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-WEBVTT
-
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- The following is a conversation with Chris Latner.
-
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- Currently, he's a senior director
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- at Google working on several projects, including CPU, GPU,
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- TPU accelerators for TensorFlow, Swift for TensorFlow,
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- and all kinds of machine learning compiler magic
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- going on behind the scenes.
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- He's one of the top experts in the world
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- on compiler technologies, which means he deeply
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- understands the intricacies of how hardware and software come
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- together to create efficient code.
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- He created the LLVM compiler infrastructure project
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- and the Clang compiler.
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- He led major engineering efforts at Apple,
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- including the creation of the Swift programming language.
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- He also briefly spent time at Tesla
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- as vice president of Autopilot software
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- during the transition from Autopilot hardware 1
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- to hardware 2, when Tesla essentially
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- started from scratch to build an in house software
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- infrastructure for Autopilot.
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- I could have easily talked to Chris for many more hours.
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- Compiling code down across the levels of abstraction
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- is one of the most fundamental and fascinating aspects
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- of what computers do, and he is one of the world
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- experts in this process.
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- It's rigorous science, and it's messy, beautiful art.
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- This conversation is part of the Artificial Intelligence
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- podcast.
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- If you enjoy it, subscribe on YouTube, iTunes,
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- or simply connect with me on Twitter at Lex Friedman,
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- spelled F R I D.
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- And now, here's my conversation with Chris Ladner.
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- What was the first program you've ever written?
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- My first program.
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- Back, and when was it?
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- I think I started as a kid, and my parents
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- got a basic programming book.
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- And so when I started, it was typing out programs
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- from a book, and seeing how they worked,
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- and then typing them in wrong, and trying
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- to figure out why they were not working right,
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- that kind of stuff.
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- So BASIC, what was the first language
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- that you remember yourself maybe falling in love with,
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- like really connecting with?
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- I don't know.
-
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- I mean, I feel like I've learned a lot along the way,
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- and each of them have a different special thing
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- about them.
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- So I started in BASIC, and then went like GW BASIC,
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- which was the thing back in the DOS days,
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-02:11.440 --> 02:15.280
- and then upgraded to QBASIC, and eventually QuickBASIC,
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- which are all slightly more fancy versions of Microsoft
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- BASIC.
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- Made the jump to Pascal, and started
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- doing machine language programming and assembly
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- in Pascal, which was really cool.
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- Turbo Pascal was amazing for its day.
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- Eventually got into C, C++, and then kind of did
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- lots of other weird things.
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- I feel like you took the dark path, which is the,
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- you could have gone Lisp.
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- Yeah.
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- You could have gone higher level sort
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- of functional philosophical hippie route.
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- Instead, you went into like the dark arts of the C.
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- It was straight into the machine.
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- Straight to the machine.
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- So I started with BASIC, Pascal, and then Assembly,
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- and then wrote a lot of Assembly.
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- And I eventually did Smalltalk and other things like that.
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- But that was not the starting point.
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- But so what is this journey to C?
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- Is that in high school?
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- Is that in college?
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- That was in high school, yeah.
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- And then that was really about trying
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- to be able to do more powerful things than what Pascal could
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- do, and also to learn a different world.
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- So he was really confusing to me with pointers
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- and the syntax and everything, and it took a while.
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- But Pascal's much more principled in various ways.
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- C is more, I mean, it has its historical roots,
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- but it's not as easy to learn.
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- With pointers, there's this memory management thing
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- that you have to become conscious of.
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- Is that the first time you start to understand
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- that there's resources that you're supposed to manage?
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- Well, so you have that in Pascal as well.
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- But in Pascal, like the caret instead of the star,
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- there's some small differences like that.
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- But it's not about pointer arithmetic.
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- And in C, you end up thinking about how things get
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- laid out in memory a lot more.
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- And so in Pascal, you have allocating and deallocating
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- and owning the memory, but just the programs are simpler,
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- and you don't have to.
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- Well, for example, Pascal has a string type.
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- And so you can think about a string
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- instead of an array of characters
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- which are consecutive in memory.
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- So it's a little bit of a higher level abstraction.
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- So let's get into it.
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- Let's talk about LLVM, C lang, and compilers.
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- Sure.
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- So can you tell me first what LLVM and C lang are?
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- And how is it that you find yourself
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- the creator and lead developer, one
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-04:35.720 --> 04:39.400
- of the most powerful compiler optimization systems
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- in use today?
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- Sure.
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- So I guess they're different things.
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- So let's start with what is a compiler?
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- Is that a good place to start?
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- What are the phases of a compiler?
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- Where are the parts?
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- Yeah, what is it?
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- So what is even a compiler used for?
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- So the way I look at this is you have a two sided problem of you
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- have humans that need to write code.
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- And then you have machines that need to run
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- the program that the human wrote.
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- And for lots of reasons, the humans
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- don't want to be writing in binary
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- and want to think about every piece of hardware.
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- And so at the same time that you have lots of humans,
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- you also have lots of kinds of hardware.
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- And so compilers are the art of allowing
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- humans to think at a level of abstraction
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- that they want to think about.
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- And then get that program, get the thing that they wrote,
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- to run on a specific piece of hardware.
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- And the interesting and exciting part of all this
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-05:29.480 --> 05:32.080
- is that there's now lots of different kinds of hardware,
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- chips like x86 and PowerPC and ARM and things like that.
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- But also high performance accelerators
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- for machine learning and other things like that
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- are also just different kinds of hardware, GPUs.
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- These are new kinds of hardware.
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- And at the same time, on the programming side of it,
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- you have basic, you have C, you have JavaScript,
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- you have Python, you have Swift.
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- You have lots of other languages
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- that are all trying to talk to the human in a different way
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- to make them more expressive and capable and powerful.
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- And so compilers are the thing
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- that goes from one to the other.
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- End to end, from the very beginning to the very end.
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- End to end.
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- And so you go from what the human wrote
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- and programming languages end up being about
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- expressing intent, not just for the compiler
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-06:14.560 --> 06:17.980
- and the hardware, but the programming language's job
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-06:17.980 --> 06:20.920
- is really to capture an expression
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- of what the programmer wanted
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- that then can be maintained and adapted
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-06:25.120 --> 06:27.120
- and evolved by other humans,
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- as well as interpreted by the compiler.
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-06:29.720 --> 06:31.560
- So when you look at this problem,
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-06:31.560 --> 06:34.200
- you have, on the one hand, humans, which are complicated.
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- And you have hardware, which is complicated.
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-06:36.760 --> 06:39.900
- And so compilers typically work in multiple phases.
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-06:39.900 --> 06:42.760
- And so the software engineering challenge
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- that you have here is try to get maximum reuse
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- out of the amount of code that you write,
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- because these compilers are very complicated.
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- And so the way it typically works out
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- is that you have something called a front end or a parser
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- that is language specific.
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- And so you'll have a C parser, and that's what Clang is,
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- or C++ or JavaScript or Python or whatever.
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- That's the front end.
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- Then you'll have a middle part,
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- which is often the optimizer.
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- And then you'll have a late part,
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- which is hardware specific.
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- And so compilers end up,
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- there's many different layers often,
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- but these three big groups are very common in compilers.
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- And what LLVM is trying to do
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- is trying to standardize that middle and last part.
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- And so one of the cool things about LLVM
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- is that there are a lot of different languages
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- that compile through to it.
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- And so things like Swift, but also Julia, Rust,
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- Clang for C, C++, Subjective C,
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- like these are all very different languages
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- and they can all use the same optimization infrastructure,
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- which gets better performance,
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- and the same code generation infrastructure
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- for hardware support.
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- And so LLVM is really that layer that is common,
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- that all these different specific compilers can use.
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-07:55.580 --> 07:59.300
- And is it a standard, like a specification,
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- or is it literally an implementation?
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- It's an implementation.
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- And so I think there's a couple of different ways
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- of looking at it, right?
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- Because it depends on which angle you're looking at it from.
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- LLVM ends up being a bunch of code, okay?
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- So it's a bunch of code that people reuse
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- and they build compilers with.
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- We call it a compiler infrastructure
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-08:18.060 --> 08:20.060
- because it's kind of the underlying platform
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- that you build a concrete compiler on top of.
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-08:22.580 --> 08:23.740
- But it's also a community.
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- And the LLVM community is hundreds of people
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- that all collaborate.
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-08:27.980 --> 08:30.620
- And one of the most fascinating things about LLVM
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-08:30.620 --> 08:34.260
- over the course of time is that we've managed somehow
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- to successfully get harsh competitors
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- in the commercial space to collaborate
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- on shared infrastructure.
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- And so you have Google and Apple,
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- you have AMD and Intel,
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-08:45.860 --> 08:48.860
- you have Nvidia and AMD on the graphics side,
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-08:48.860 --> 08:52.620
- you have Cray and everybody else doing these things.
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-08:52.620 --> 08:55.420
- And all these companies are collaborating together
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- to make that shared infrastructure really, really great.
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-08:58.520 --> 09:01.380
- And they do this not out of the goodness of their heart,
-
-09:01.380 --> 09:03.420
- but they do it because it's in their commercial interest
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- of having really great infrastructure
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- that they can build on top of
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-09:06.740 --> 09:09.080
- and facing the reality that it's so expensive
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- that no one company, even the big companies,
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- no one company really wants to implement it all themselves.
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- Expensive or difficult?
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- Both.
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-09:16.940 --> 09:20.540
- That's a great point because it's also about the skill sets.
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- And the skill sets are very hard to find.
-
-09:26.020 --> 09:27.980
- How big is the LLVM?
-
-09:27.980 --> 09:30.780
- It always seems like with open source projects,
-
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- the kind, an LLVM is open source?
-
-09:33.500 --> 09:34.420
- Yes, it's open source.
-
-09:34.420 --> 09:38.660
- It's about, it's 19 years old now, so it's fairly old.
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-09:38.660 --> 09:40.940
- It seems like the magic often happens
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-09:40.940 --> 09:43.020
- within a very small circle of people.
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- Yes.
-
-09:43.860 --> 09:46.060
- At least their early birth and whatever.
-
-09:46.060 --> 09:49.660
- Yes, so the LLVM came from a university project,
-
-09:49.660 --> 09:51.540
- and so I was at the University of Illinois.
-
-09:51.540 --> 09:53.900
- And there it was myself, my advisor,
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-09:53.900 --> 09:57.500
- and then a team of two or three research students
-
-09:57.500 --> 09:58.380
- in the research group,
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-09:58.380 --> 10:02.100
- and we built many of the core pieces initially.
-
-10:02.100 --> 10:03.740
- I then graduated and went to Apple,
-
-10:03.740 --> 10:06.480
- and at Apple brought it to the products,
-
-10:06.480 --> 10:09.340
- first in the OpenGL graphics stack,
-
-10:09.340 --> 10:11.580
- but eventually to the C compiler realm,
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-10:11.580 --> 10:12.780
- and eventually built Clang,
-
-10:12.780 --> 10:14.640
- and eventually built Swift and these things.
-
-10:14.640 --> 10:16.380
- Along the way, building a team of people
-
-10:16.380 --> 10:18.620
- that are really amazing compiler engineers
-
-10:18.620 --> 10:20.060
- that helped build a lot of that.
-
-10:20.060 --> 10:21.860
- And so as it was gaining momentum
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-10:21.860 --> 10:24.780
- and as Apple was using it, being open source and public
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-10:24.780 --> 10:26.440
- and encouraging contribution,
-
-10:26.440 --> 10:28.780
- many others, for example, at Google,
-
-10:28.780 --> 10:30.220
- came in and started contributing.
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-10:30.220 --> 10:33.740
- And in some cases, Google effectively owns Clang now
-
-10:33.740 --> 10:35.540
- because it cares so much about C++
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-10:35.540 --> 10:37.340
- and the evolution of that ecosystem,
-
-10:37.340 --> 10:41.420
- and so it's investing a lot in the C++ world
-
-10:41.420 --> 10:42.980
- and the tooling and things like that.
-
-10:42.980 --> 10:47.860
- And so likewise, NVIDIA cares a lot about CUDA.
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-10:47.860 --> 10:50.780
- And so CUDA uses Clang and uses LLVM
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-10:50.780 --> 10:54.060
- for graphics and GPGPU.
-
-10:54.060 --> 10:58.940
- And so when you first started as a master's project,
-
-10:58.940 --> 11:02.980
- I guess, did you think it was gonna go as far as it went?
-
-11:02.980 --> 11:06.340
- Were you crazy ambitious about it?
-
-11:06.340 --> 11:07.180
- No.
-
-11:07.180 --> 11:09.840
- It seems like a really difficult undertaking, a brave one.
-
-11:09.840 --> 11:11.380
- Yeah, no, no, no, it was nothing like that.
-
-11:11.380 --> 11:13.740
- So my goal when I went to the University of Illinois
-
-11:13.740 --> 11:17.540
- was to get in and out with a non thesis masters in a year
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-11:17.540 --> 11:18.720
- and get back to work.
-
-11:18.720 --> 11:22.200
- So I was not planning to stay for five years
-
-11:22.200 --> 11:24.460
- and build this massive infrastructure.
-
-11:24.460 --> 11:27.380
- I got nerd sniped into staying.
-
-11:27.380 --> 11:29.580
- And a lot of it was because LLVM was fun
-
-11:29.580 --> 11:30.900
- and I was building cool stuff
-
-11:30.900 --> 11:33.420
- and learning really interesting things
-
-11:33.420 --> 11:36.900
- and facing both software engineering challenges,
-
-11:36.900 --> 11:38.540
- but also learning how to work in a team
-
-11:38.540 --> 11:40.100
- and things like that.
-
-11:40.100 --> 11:43.620
- I had worked at many companies as interns before that,
-
-11:43.620 --> 11:45.860
- but it was really a different thing
-
-11:45.860 --> 11:48.060
- to have a team of people that are working together
-
-11:48.060 --> 11:50.460
- and try and collaborate in version control.
-
-11:50.460 --> 11:52.420
- And it was just a little bit different.
-
-11:52.420 --> 11:54.060
- Like I said, I just talked to Don Knuth
-
-11:54.060 --> 11:56.860
- and he believes that 2% of the world population
-
-11:56.860 --> 11:58.820
- have something weird with their brain,
-
-11:58.820 --> 12:01.100
- that they're geeks, they understand computers,
-
-12:01.100 --> 12:02.580
- they're connected with computers.
-
-12:02.580 --> 12:04.380
- He put it at exactly 2%.
-
-12:04.380 --> 12:05.540
- Okay, so.
-
-12:05.540 --> 12:06.580
- He's a specific guy.
-
-12:06.580 --> 12:08.780
- It's very specific.
-
-12:08.780 --> 12:10.180
- Well, he says, I can't prove it,
-
-12:10.180 --> 12:11.780
- but it's very empirically there.
-
-12:13.180 --> 12:14.500
- Is there something that attracts you
-
-12:14.500 --> 12:16.940
- to the idea of optimizing code?
-
-12:16.940 --> 12:19.180
- And he seems like that's one of the biggest,
-
-12:19.180 --> 12:20.900
- coolest things about LLVM.
-
-12:20.900 --> 12:22.500
- Yeah, that's one of the major things it does.
-
-12:22.500 --> 12:26.460
- So I got into that because of a person, actually.
-
-12:26.460 --> 12:28.220
- So when I was in my undergraduate,
-
-12:28.220 --> 12:32.060
- I had an advisor, or a professor named Steve Vegdahl.
-
-12:32.060 --> 12:35.740
- And he, I went to this little tiny private school.
-
-12:35.740 --> 12:38.300
- There were like seven or nine people
-
-12:38.300 --> 12:40.340
- in my computer science department,
-
-12:40.340 --> 12:43.100
- students in my class.
-
-12:43.100 --> 12:47.460
- So it was a very tiny, very small school.
-
-12:47.460 --> 12:49.940
- It was kind of a wart on the side of the math department
-
-12:49.940 --> 12:51.260
- kind of a thing at the time.
-
-12:51.260 --> 12:53.820
- I think it's evolved a lot in the many years since then.
-
-12:53.820 --> 12:58.300
- But Steve Vegdahl was a compiler guy.
-
-12:58.300 --> 12:59.580
- And he was super passionate.
-
-12:59.580 --> 13:02.740
- And his passion rubbed off on me.
-
-13:02.740 --> 13:04.460
- And one of the things I like about compilers
-
-13:04.460 --> 13:09.100
- is that they're large, complicated software pieces.
-
-13:09.100 --> 13:12.940
- And so one of the culminating classes
-
-13:12.940 --> 13:14.540
- that many computer science departments,
-
-13:14.540 --> 13:16.700
- at least at the time, did was to say
-
-13:16.700 --> 13:18.380
- that you would take algorithms and data structures
-
-13:18.380 --> 13:19.460
- and all these core classes.
-
-13:19.460 --> 13:21.740
- But then the compilers class was one of the last classes
-
-13:21.740 --> 13:24.380
- you take because it pulls everything together.
-
-13:24.380 --> 13:26.980
- And then you work on one piece of code
-
-13:26.980 --> 13:28.700
- over the entire semester.
-
-13:28.700 --> 13:32.180
- And so you keep building on your own work,
-
-13:32.180 --> 13:33.460
- which is really interesting.
-
-13:33.460 --> 13:36.060
- And it's also very challenging because in many classes,
-
-13:36.060 --> 13:38.380
- if you don't get a project done, you just forget about it
-
-13:38.380 --> 13:41.300
- and move on to the next one and get your B or whatever it is.
-
-13:41.300 --> 13:43.860
- But here you have to live with the decisions you make
-
-13:43.860 --> 13:45.220
- and continue to reinvest in it.
-
-13:45.220 --> 13:48.500
- And I really like that.
-
-13:48.500 --> 13:50.700
- And so I did an extra study project
-
-13:50.700 --> 13:52.420
- with him the following semester.
-
-13:52.420 --> 13:53.940
- And he was just really great.
-
-13:53.940 --> 13:56.860
- And he was also a great mentor in a lot of ways.
-
-13:56.860 --> 13:59.500
- And so from him and from his advice,
-
-13:59.500 --> 14:01.380
- he encouraged me to go to graduate school.
-
-14:01.380 --> 14:03.420
- I wasn't super excited about going to grad school.
-
-14:03.420 --> 14:05.540
- I wanted the master's degree, but I
-
-14:05.540 --> 14:08.940
- didn't want to be an academic.
-
-14:08.940 --> 14:11.100
- But like I said, I kind of got tricked into saying
-
-14:11.100 --> 14:12.180
- and was having a lot of fun.
-
-14:12.180 --> 14:14.540
- And I definitely do not regret it.
-
-14:14.540 --> 14:17.940
- What aspects of compilers were the things you connected with?
-
-14:17.940 --> 14:22.100
- So LLVM, there's also the other part
-
-14:22.100 --> 14:24.940
- that's really interesting if you're interested in languages
-
-14:24.940 --> 14:29.620
- is parsing and just analyzing the language,
-
-14:29.620 --> 14:31.220
- breaking it down, parsing, and so on.
-
-14:31.220 --> 14:32.580
- Was that interesting to you, or were you
-
-14:32.580 --> 14:34.060
- more interested in optimization?
-
-14:34.060 --> 14:37.420
- For me, it was more so I'm not really a math person.
-
-14:37.420 --> 14:38.180
- I could do math.
-
-14:38.180 --> 14:41.540
- I understand some bits of it when I get into it.
-
-14:41.540 --> 14:43.940
- But math is never the thing that attracted me.
-
-14:43.940 --> 14:46.100
- And so a lot of the parser part of the compiler
-
-14:46.100 --> 14:47.820
- has a lot of good formal theories
-
-14:47.820 --> 14:50.060
- that Don, for example, knows quite well.
-
-14:50.060 --> 14:51.540
- I'm still waiting for his book on that.
-
-14:54.740 --> 14:57.900
- But I just like building a thing and seeing what it could do
-
-14:57.900 --> 15:00.740
- and exploring and getting it to do more things
-
-15:00.740 --> 15:04.020
- and then setting new goals and reaching for them.
-
-15:04.020 --> 15:09.580
- And in the case of LLVM, when I started working on that,
-
-15:09.580 --> 15:13.420
- my research advisor that I was working for was a compiler guy.
-
-15:13.420 --> 15:15.620
- And so he and I specifically found each other
-
-15:15.620 --> 15:16.940
- because we were both interested in compilers.
-
-15:16.940 --> 15:19.500
- And so I started working with him and taking his class.
-
-15:19.500 --> 15:21.580
- And a lot of LLVM initially was, it's
-
-15:21.580 --> 15:24.380
- fun implementing all the standard algorithms and all
-
-15:24.380 --> 15:26.380
- the things that people had been talking about
-
-15:26.380 --> 15:27.220
- and were well known.
-
-15:27.220 --> 15:30.620
- And they were in the curricula for advanced studies
-
-15:30.620 --> 15:31.340
- and compilers.
-
-15:31.340 --> 15:34.580
- And so just being able to build that was really fun.
-
-15:34.580 --> 15:37.660
- And I was learning a lot by, instead of reading about it,
-
-15:37.660 --> 15:38.660
- just building.
-
-15:38.660 --> 15:40.220
- And so I enjoyed that.
-
-15:40.220 --> 15:42.820
- So you said compilers are these complicated systems.
-
-15:42.820 --> 15:46.180
- Can you even just with language try
-
-15:46.180 --> 15:52.220
- to describe how you turn a C++ program into code?
-
-15:52.220 --> 15:53.460
- Like, what are the hard parts?
-
-15:53.460 --> 15:54.620
- Why is it so hard?
-
-15:54.620 --> 15:57.020
- So I'll give you examples of the hard parts along the way.
-
-15:57.020 --> 16:01.060
- So C++ is a very complicated programming language.
-
-16:01.060 --> 16:03.500
- It's something like 1,400 pages in the spec.
-
-16:03.500 --> 16:06.060
- So C++ by itself is crazy complicated.
-
-16:06.060 --> 16:07.140
- Can we just pause?
-
-16:07.140 --> 16:09.140
- What makes the language complicated in terms
-
-16:09.140 --> 16:12.340
- of what's syntactically?
-
-16:12.340 --> 16:14.300
- So it's what they call syntax.
-
-16:14.300 --> 16:16.700
- So the actual how the characters are arranged, yes.
-
-16:16.700 --> 16:20.020
- It's also semantics, how it behaves.
-
-16:20.020 --> 16:21.900
- It's also, in the case of C++, there's
-
-16:21.900 --> 16:23.380
- a huge amount of history.
-
-16:23.380 --> 16:26.700
- C++ is built on top of C. You play that forward.
-
-16:26.700 --> 16:29.860
- And then a bunch of suboptimal, in some cases, decisions
-
-16:29.860 --> 16:31.620
- were made, and they compound.
-
-16:31.620 --> 16:33.380
- And then more and more and more things
-
-16:33.380 --> 16:36.980
- keep getting added to C++, and it will probably never stop.
-
-16:36.980 --> 16:38.540
- But the language is very complicated
-
-16:38.540 --> 16:39.540
- from that perspective.
-
-16:39.540 --> 16:41.200
- And so the interactions between subsystems
-
-16:41.200 --> 16:42.420
- is very complicated.
-
-16:42.420 --> 16:43.580
- There's just a lot there.
-
-16:43.580 --> 16:45.660
- And when you talk about the front end,
-
-16:45.660 --> 16:47.060
- one of the major challenges, which
-
-16:47.060 --> 16:51.140
- clang as a project, the C, C++ compiler that I built,
-
-16:51.140 --> 16:54.480
- I and many people built, one of the challenges we took on
-
-16:54.480 --> 16:57.780
- was we looked at GCC.
-
-16:57.780 --> 17:02.540
- GCC, at the time, was a really good industry standardized
-
-17:02.540 --> 17:05.260
- compiler that had really consolidated
-
-17:05.260 --> 17:08.340
- a lot of the other compilers in the world and was a standard.
-
-17:08.340 --> 17:10.620
- But it wasn't really great for research.
-
-17:10.620 --> 17:12.580
- The design was very difficult to work with.
-
-17:12.580 --> 17:16.620
- And it was full of global variables and other things
-
-17:16.620 --> 17:18.540
- that made it very difficult to reuse in ways
-
-17:18.540 --> 17:20.420
- that it wasn't originally designed for.
-
-17:20.420 --> 17:22.740
- And so with clang, one of the things that we wanted to do
-
-17:22.740 --> 17:25.500
- is push forward on better user interface,
-
-17:25.500 --> 17:28.060
- so make error messages that are just better than GCC's.
-
-17:28.060 --> 17:29.580
- And that's actually hard, because you
-
-17:29.580 --> 17:32.780
- have to do a lot of bookkeeping in an efficient way
-
-17:32.780 --> 17:33.700
- to be able to do that.
-
-17:33.700 --> 17:35.180
- We want to make compile time better.
-
-17:35.180 --> 17:37.500
- And so compile time is about making it efficient,
-
-17:37.500 --> 17:38.900
- which is also really hard when you're keeping
-
-17:38.900 --> 17:40.540
- track of extra information.
-
-17:40.540 --> 17:43.380
- We wanted to make new tools available,
-
-17:43.380 --> 17:46.380
- so refactoring tools and other analysis tools
-
-17:46.380 --> 17:50.540
- that GCC never supported, also leveraging the extra information
-
-17:50.540 --> 17:54.060
- we kept, but enabling those new classes of tools
-
-17:54.060 --> 17:55.940
- that then get built into IDEs.
-
-17:55.940 --> 17:59.380
- And so that's been one of the areas that clang has really
-
-17:59.380 --> 18:01.300
- helped push the world forward in,
-
-18:01.300 --> 18:05.060
- is in the tooling for C and C++ and things like that.
-
-18:05.060 --> 18:07.500
- But C++ and the front end piece is complicated.
-
-18:07.500 --> 18:09.000
- And you have to build syntax trees.
-
-18:09.000 --> 18:11.340
- And you have to check every rule in the spec.
-
-18:11.340 --> 18:14.020
- And you have to turn that back into an error message
-
-18:14.020 --> 18:16.020
- to the human that the human can understand
-
-18:16.020 --> 18:17.820
- when they do something wrong.
-
-18:17.820 --> 18:20.740
- But then you start doing what's called lowering,
-
-18:20.740 --> 18:23.060
- so going from C++ and the way that it represents
-
-18:23.060 --> 18:24.980
- code down to the machine.
-
-18:24.980 --> 18:27.380
- And when you do that, there's many different phases
-
-18:27.380 --> 18:29.660
- you go through.
-
-18:29.660 --> 18:33.020
- Often, there are, I think LLVM has something like 150
-
-18:33.020 --> 18:36.260
- different what are called passes in the compiler
-
-18:36.260 --> 18:38.780
- that the code passes through.
-
-18:38.780 --> 18:41.860
- And these get organized in very complicated ways,
-
-18:41.860 --> 18:44.360
- which affect the generated code and the performance
-
-18:44.360 --> 18:45.980
- and compile time and many other things.
-
-18:45.980 --> 18:47.300
- What are they passing through?
-
-18:47.300 --> 18:53.980
- So after you do the clang parsing, what's the graph?
-
-18:53.980 --> 18:54.900
- What does it look like?
-
-18:54.900 --> 18:56.100
- What's the data structure here?
-
-18:56.100 --> 18:59.060
- Yeah, so in the parser, it's usually a tree.
-
-18:59.060 --> 19:01.100
- And it's called an abstract syntax tree.
-
-19:01.100 --> 19:04.580
- And so the idea is you have a node for the plus
-
-19:04.580 --> 19:06.820
- that the human wrote in their code.
-
-19:06.820 --> 19:09.020
- Or the function call, you'll have a node for call
-
-19:09.020 --> 19:11.900
- with the function that they call and the arguments they pass,
-
-19:11.900 --> 19:14.460
- things like that.
-
-19:14.460 --> 19:16.620
- This then gets lowered into what's
-
-19:16.620 --> 19:18.620
- called an intermediate representation.
-
-19:18.620 --> 19:22.100
- And intermediate representations are like LLVM has one.
-
-19:22.100 --> 19:26.940
- And there, it's what's called a control flow graph.
-
-19:26.940 --> 19:31.220
- And so you represent each operation in the program
-
-19:31.220 --> 19:34.480
- as a very simple, like this is going to add two numbers.
-
-19:34.480 --> 19:35.980
- This is going to multiply two things.
-
-19:35.980 --> 19:37.460
- Maybe we'll do a call.
-
-19:37.460 --> 19:40.260
- But then they get put in what are called blocks.
-
-19:40.260 --> 19:43.580
- And so you get blocks of these straight line operations,
-
-19:43.580 --> 19:45.340
- where instead of being nested like in a tree,
-
-19:45.340 --> 19:46.900
- it's straight line operations.
-
-19:46.900 --> 19:49.780
- And so there's a sequence and an ordering to these operations.
-
-19:49.780 --> 19:51.820
- So within the block or outside the block?
-
-19:51.820 --> 19:52.980
- That's within the block.
-
-19:52.980 --> 19:54.980
- And so it's a straight line sequence of operations
-
-19:54.980 --> 19:55.740
- within the block.
-
-19:55.740 --> 19:58.980
- And then you have branches, like conditional branches,
-
-19:58.980 --> 20:00.140
- between blocks.
-
-20:00.140 --> 20:04.860
- And so when you write a loop, for example, in a syntax tree,
-
-20:04.860 --> 20:08.060
- you would have a for node, like for a for statement
-
-20:08.060 --> 20:10.540
- in a C like language, you'd have a for node.
-
-20:10.540 --> 20:12.200
- And you have a pointer to the expression
-
-20:12.200 --> 20:14.080
- for the initializer, a pointer to the expression
-
-20:14.080 --> 20:16.040
- for the increment, a pointer to the expression
-
-20:16.040 --> 20:18.900
- for the comparison, a pointer to the body.
-
-20:18.900 --> 20:21.060
- And these are all nested underneath it.
-
-20:21.060 --> 20:22.900
- In a control flow graph, you get a block
-
-20:22.900 --> 20:26.820
- for the code that runs before the loop, so the initializer
-
-20:26.820 --> 20:27.620
- code.
-
-20:27.620 --> 20:30.340
- And you have a block for the body of the loop.
-
-20:30.340 --> 20:33.780
- And so the body of the loop code goes in there,
-
-20:33.780 --> 20:35.660
- but also the increment and other things like that.
-
-20:35.660 --> 20:37.860
- And then you have a branch that goes back to the top
-
-20:37.860 --> 20:39.900
- and a comparison and a branch that goes out.
-
-20:39.900 --> 20:43.820
- And so it's more of an assembly level kind of representation.
-
-20:43.820 --> 20:46.060
- But the nice thing about this level of representation
-
-20:46.060 --> 20:48.700
- is it's much more language independent.
-
-20:48.700 --> 20:51.900
- And so there's lots of different kinds of languages
-
-20:51.900 --> 20:54.540
- with different kinds of, you know,
-
-20:54.540 --> 20:56.840
- JavaScript has a lot of different ideas of what
-
-20:56.840 --> 20:58.180
- is false, for example.
-
-20:58.180 --> 21:00.780
- And all that can stay in the front end.
-
-21:00.780 --> 21:04.220
- But then that middle part can be shared across all those.
-
-21:04.220 --> 21:07.540
- How close is that intermediate representation
-
-21:07.540 --> 21:10.620
- to neural networks, for example?
-
-21:10.620 --> 21:13.540
- Are they, because everything you describe
-
-21:13.540 --> 21:16.100
- is a kind of echoes of a neural network graph.
-
-21:16.100 --> 21:18.940
- Are they neighbors or what?
-
-21:18.940 --> 21:20.980
- They're quite different in details,
-
-21:20.980 --> 21:22.520
- but they're very similar in idea.
-
-21:22.520 --> 21:24.320
- So one of the things that neural networks do
-
-21:24.320 --> 21:26.900
- is they learn representations for data
-
-21:26.900 --> 21:29.140
- at different levels of abstraction.
-
-21:29.140 --> 21:33.940
- And then they transform those through layers, right?
-
-21:33.940 --> 21:35.660
- So the compiler does very similar things.
-
-21:35.660 --> 21:37.320
- But one of the things the compiler does
-
-21:37.320 --> 21:40.660
- is it has relatively few different representations.
-
-21:40.660 --> 21:43.100
- Where a neural network often, as you get deeper, for example,
-
-21:43.100 --> 21:44.820
- you get many different representations
-
-21:44.820 --> 21:47.380
- in each layer or set of ops.
-
-21:47.380 --> 21:50.260
- It's transforming between these different representations.
-
-21:50.260 --> 21:53.100
- In a compiler, often you get one representation
-
-21:53.100 --> 21:55.240
- and they do many transformations to it.
-
-21:55.240 --> 21:59.540
- And these transformations are often applied iteratively.
-
-21:59.540 --> 22:02.940
- And for programmers, there's familiar types of things.
-
-22:02.940 --> 22:06.180
- For example, trying to find expressions inside of a loop
-
-22:06.180 --> 22:08.540
- and pulling them out of a loop so they execute for times.
-
-22:08.540 --> 22:10.740
- Or find redundant computation.
-
-22:10.740 --> 22:15.380
- Or find constant folding or other simplifications,
-
-22:15.380 --> 22:19.060
- turning two times x into x shift left by one.
-
-22:19.060 --> 22:21.980
- And things like this are all the examples
-
-22:21.980 --> 22:23.340
- of the things that happen.
-
-22:23.340 --> 22:26.180
- But compilers end up getting a lot of theorem proving
-
-22:26.180 --> 22:27.760
- and other kinds of algorithms that
-
-22:27.760 --> 22:30.100
- try to find higher level properties of the program that
-
-22:30.100 --> 22:32.280
- then can be used by the optimizer.
-
-22:32.280 --> 22:32.780
- Cool.
-
-22:32.780 --> 22:38.140
- So what's the biggest bang for the buck with optimization?
-
-22:38.140 --> 22:38.640
- Today?
-
-22:38.640 --> 22:39.140
- Yeah.
-
-22:39.140 --> 22:40.900
- Well, no, not even today.
-
-22:40.900 --> 22:42.900
- At the very beginning, the 80s, I don't know.
-
-22:42.900 --> 22:44.300
- Yeah, so for the 80s, a lot of it
-
-22:44.300 --> 22:46.420
- was things like register allocation.
-
-22:46.420 --> 22:50.460
- So the idea of in a modern microprocessor,
-
-22:50.460 --> 22:51.880
- what you'll end up having is you'll
-
-22:51.880 --> 22:54.340
- end up having memory, which is relatively slow.
-
-22:54.340 --> 22:57.060
- And then you have registers that are relatively fast.
-
-22:57.060 --> 23:00.340
- But registers, you don't have very many of them.
-
-23:00.340 --> 23:02.600
- And so when you're writing a bunch of code,
-
-23:02.600 --> 23:04.180
- you're just saying, compute this,
-
-23:04.180 --> 23:05.940
- put in a temporary variable, compute this, compute this,
-
-23:05.940 --> 23:07.780
- compute this, put in a temporary variable.
-
-23:07.780 --> 23:08.220
- I have a loop.
-
-23:08.220 --> 23:09.780
- I have some other stuff going on.
-
-23:09.780 --> 23:11.660
- Well, now you're running on an x86,
-
-23:11.660 --> 23:13.900
- like a desktop PC or something.
-
-23:13.900 --> 23:16.860
- Well, it only has, in some cases, some modes,
-
-23:16.860 --> 23:18.700
- eight registers.
-
-23:18.700 --> 23:21.620
- And so now the compiler has to choose what values get
-
-23:21.620 --> 23:24.820
- put in what registers at what points in the program.
-
-23:24.820 --> 23:26.580
- And this is actually a really big deal.
-
-23:26.580 --> 23:29.500
- So if you think about, you have a loop, an inner loop
-
-23:29.500 --> 23:31.620
- that executes millions of times maybe.
-
-23:31.620 --> 23:33.620
- If you're doing loads and stores inside that loop,
-
-23:33.620 --> 23:35.040
- then it's going to be really slow.
-
-23:35.040 --> 23:37.740
- But if you can somehow fit all the values inside that loop
-
-23:37.740 --> 23:40.180
- in registers, now it's really fast.
-
-23:40.180 --> 23:43.020
- And so getting that right requires a lot of work,
-
-23:43.020 --> 23:44.940
- because there's many different ways to do that.
-
-23:44.940 --> 23:46.980
- And often what the compiler ends up doing
-
-23:46.980 --> 23:48.840
- is it ends up thinking about things
-
-23:48.840 --> 23:52.020
- in a different representation than what the human wrote.
-
-23:52.020 --> 23:53.340
- You wrote into x.
-
-23:53.340 --> 23:56.820
- Well, the compiler thinks about that as four different values,
-
-23:56.820 --> 23:59.280
- each which have different lifetimes across the function
-
-23:59.280 --> 24:00.420
- that it's in.
-
-24:00.420 --> 24:03.180
- And each of those could be put in a register or memory
-
-24:03.180 --> 24:06.140
- or different memory or maybe in some parts of the code
-
-24:06.140 --> 24:08.360
- recomputed instead of stored and reloaded.
-
-24:08.360 --> 24:10.700
- And there are many of these different kinds of techniques
-
-24:10.700 --> 24:11.460
- that can be used.
-
-24:11.460 --> 24:15.780
- So it's adding almost like a time dimension to it's
-
-24:15.780 --> 24:18.300
- trying to optimize across time.
-
-24:18.300 --> 24:20.340
- So it's considering when you're programming,
-
-24:20.340 --> 24:21.860
- you're not thinking in that way.
-
-24:21.860 --> 24:23.220
- Yeah, absolutely.
-
-24:23.220 --> 24:27.100
- And so the RISC era made things.
-
-24:27.100 --> 24:32.020
- So RISC chips, R I S C. The RISC chips,
-
-24:32.020 --> 24:33.740
- as opposed to CISC chips.
-
-24:33.740 --> 24:36.700
- The RISC chips made things more complicated for the compiler,
-
-24:36.700 --> 24:40.660
- because what they ended up doing is ending up
-
-24:40.660 --> 24:42.500
- adding pipelines to the processor, where
-
-24:42.500 --> 24:45.020
- the processor can do more than one thing at a time.
-
-24:45.020 --> 24:47.740
- But this means that the order of operations matters a lot.
-
-24:47.740 --> 24:50.260
- So one of the classical compiler techniques that you use
-
-24:50.260 --> 24:51.940
- is called scheduling.
-
-24:51.940 --> 24:54.220
- And so moving the instructions around
-
-24:54.220 --> 24:57.740
- so that the processor can keep its pipelines full instead
-
-24:57.740 --> 24:59.220
- of stalling and getting blocked.
-
-24:59.220 --> 25:01.180
- And so there's a lot of things like that that
-
-25:01.180 --> 25:03.620
- are kind of bread and butter compiler techniques
-
-25:03.620 --> 25:06.220
- that have been studied a lot over the course of decades now.
-
-25:06.220 --> 25:08.540
- But the engineering side of making them real
-
-25:08.540 --> 25:10.580
- is also still quite hard.
-
-25:10.580 --> 25:12.460
- And you talk about machine learning.
-
-25:12.460 --> 25:14.420
- This is a huge opportunity for machine learning,
-
-25:14.420 --> 25:17.620
- because many of these algorithms are full of these
-
-25:17.620 --> 25:19.300
- hokey, hand rolled heuristics, which
-
-25:19.300 --> 25:21.820
- work well on specific benchmarks that don't generalize,
-
-25:21.820 --> 25:23.940
- and full of magic numbers.
-
-25:23.940 --> 25:26.620
- And I hear there's some techniques that
-
-25:26.620 --> 25:28.060
- are good at handling that.
-
-25:28.060 --> 25:32.220
- So what would be the, if you were to apply machine learning
-
-25:32.220 --> 25:34.740
- to this, what's the thing you're trying to optimize?
-
-25:34.740 --> 25:39.100
- Is it ultimately the running time?
-
-25:39.100 --> 25:41.180
- You can pick your metric, and there's running time,
-
-25:41.180 --> 25:43.900
- there's memory use, there's lots of different things
-
-25:43.900 --> 25:44.940
- that you can optimize for.
-
-25:44.940 --> 25:47.220
- Code size is another one that some people care about
-
-25:47.220 --> 25:48.860
- in the embedded space.
-
-25:48.860 --> 25:51.700
- Is this like the thinking into the future,
-
-25:51.700 --> 25:54.500
- or has somebody actually been crazy enough
-
-25:54.500 --> 25:58.060
- to try to have machine learning based parameter
-
-25:58.060 --> 26:01.060
- tuning for the optimization of compilers?
-
-26:01.060 --> 26:04.860
- So this is something that is, I would say, research right now.
-
-26:04.860 --> 26:06.820
- There are a lot of research systems
-
-26:06.820 --> 26:09.100
- that have been applying search in various forms.
-
-26:09.100 --> 26:11.460
- And using reinforcement learning is one form,
-
-26:11.460 --> 26:14.460
- but also brute force search has been tried for quite a while.
-
-26:14.460 --> 26:18.180
- And usually, these are in small problem spaces.
-
-26:18.180 --> 26:21.900
- So find the optimal way to code generate a matrix
-
-26:21.900 --> 26:24.460
- multiply for a GPU, something like that,
-
-26:24.460 --> 26:28.580
- where you say, there, there's a lot of design space of,
-
-26:28.580 --> 26:29.900
- do you unroll loops a lot?
-
-26:29.900 --> 26:32.660
- Do you execute multiple things in parallel?
-
-26:32.660 --> 26:35.340
- And there's many different confounding factors here
-
-26:35.340 --> 26:38.100
- because graphics cards have different numbers of threads
-
-26:38.100 --> 26:41.020
- and registers and execution ports and memory bandwidth
-
-26:41.020 --> 26:42.740
- and many different constraints that interact
-
-26:42.740 --> 26:44.460
- in nonlinear ways.
-
-26:44.460 --> 26:46.500
- And so search is very powerful for that.
-
-26:46.500 --> 26:49.820
- And it gets used in certain ways,
-
-26:49.820 --> 26:51.220
- but it's not very structured.
-
-26:51.220 --> 26:52.620
- This is something that we need,
-
-26:52.620 --> 26:54.500
- we as an industry need to fix.
-
-26:54.500 --> 26:59.220
- So you said 80s, but like, so have there been like big jumps
-
-26:59.220 --> 27:01.260
- in improvement and optimization?
-
-27:01.260 --> 27:02.340
- Yeah.
-
-27:02.340 --> 27:05.300
- Yeah, since then, what's the coolest thing?
-
-27:05.300 --> 27:07.100
- It's largely been driven by hardware.
-
-27:07.100 --> 27:09.860
- So, well, it's hardware and software.
-
-27:09.860 --> 27:13.700
- So in the mid nineties, Java totally changed the world,
-
-27:13.700 --> 27:14.540
- right?
-
-27:14.540 --> 27:17.540
- And I'm still amazed by how much change was introduced
-
-27:17.540 --> 27:19.340
- by the way or in a good way.
-
-27:19.340 --> 27:22.420
- So like reflecting back, Java introduced things like,
-
-27:22.420 --> 27:25.860
- all at once introduced things like JIT compilation.
-
-27:25.860 --> 27:27.780
- None of these were novel, but it pulled it together
-
-27:27.780 --> 27:30.580
- and made it mainstream and made people invest in it.
-
-27:30.580 --> 27:33.620
- JIT compilation, garbage collection, portable code,
-
-27:33.620 --> 27:36.620
- safe code, like memory safe code,
-
-27:36.620 --> 27:41.380
- like a very dynamic dispatch execution model.
-
-27:41.380 --> 27:42.620
- Like many of these things,
-
-27:42.620 --> 27:44.060
- which had been done in research systems
-
-27:44.060 --> 27:46.900
- and had been done in small ways in various places,
-
-27:46.900 --> 27:47.980
- really came to the forefront,
-
-27:47.980 --> 27:49.740
- really changed how things worked
-
-27:49.740 --> 27:51.980
- and therefore changed the way people thought
-
-27:51.980 --> 27:53.060
- about the problem.
-
-27:53.060 --> 27:56.300
- JavaScript was another major world change
-
-27:56.300 --> 27:57.740
- based on the way it works.
-
-27:59.300 --> 28:01.300
- But also on the hardware side of things,
-
-28:01.300 --> 28:06.300
- multi core and vector instructions really change
-
-28:06.660 --> 28:08.380
- the problem space and are very,
-
-28:09.460 --> 28:10.820
- they don't remove any of the problems
-
-28:10.820 --> 28:12.380
- that compilers faced in the past,
-
-28:12.380 --> 28:14.540
- but they add new kinds of problems
-
-28:14.540 --> 28:16.380
- of how do you find enough work
-
-28:16.380 --> 28:20.020
- to keep a four wide vector busy, right?
-
-28:20.020 --> 28:22.660
- Or if you're doing a matrix multiplication,
-
-28:22.660 --> 28:25.860
- how do you do different columns out of that matrix
-
-28:25.860 --> 28:26.700
- at the same time?
-
-28:26.700 --> 28:30.140
- And how do you maximally utilize the arithmetic compute
-
-28:30.140 --> 28:31.460
- that one core has?
-
-28:31.460 --> 28:33.500
- And then how do you take it to multiple cores?
-
-28:33.500 --> 28:35.780
- How did the whole virtual machine thing change
-
-28:35.780 --> 28:38.020
- the compilation pipeline?
-
-28:38.020 --> 28:40.460
- Yeah, so what the Java virtual machine does
-
-28:40.460 --> 28:44.180
- is it splits, just like I was talking about before,
-
-28:44.180 --> 28:46.300
- where you have a front end that parses the code,
-
-28:46.300 --> 28:48.020
- and then you have an intermediate representation
-
-28:48.020 --> 28:49.460
- that gets transformed.
-
-28:49.460 --> 28:51.020
- What Java did was they said,
-
-28:51.020 --> 28:53.100
- we will parse the code and then compile to
-
-28:53.100 --> 28:55.500
- what's known as Java byte code.
-
-28:55.500 --> 28:58.580
- And that byte code is now a portable code representation
-
-28:58.580 --> 29:02.420
- that is industry standard and locked down and can't change.
-
-29:02.420 --> 29:05.100
- And then the back part of the compiler
-
-29:05.100 --> 29:07.300
- that does optimization and code generation
-
-29:07.300 --> 29:09.460
- can now be built by different vendors.
-
-29:09.460 --> 29:10.300
- Okay.
-
-29:10.300 --> 29:13.020
- And Java byte code can be shipped around across the wire.
-
-29:13.020 --> 29:15.860
- It's memory safe and relatively trusted.
-
-29:16.860 --> 29:18.660
- And because of that, it can run in the browser.
-
-29:18.660 --> 29:20.540
- And that's why it runs in the browser, right?
-
-29:20.540 --> 29:22.980
- And so that way you can be in,
-
-29:22.980 --> 29:25.020
- again, back in the day, you would write a Java applet
-
-29:25.020 --> 29:29.300
- and as a web developer, you'd build this mini app
-
-29:29.300 --> 29:30.860
- that would run on a webpage.
-
-29:30.860 --> 29:33.620
- Well, a user of that is running a web browser
-
-29:33.620 --> 29:34.460
- on their computer.
-
-29:34.460 --> 29:37.860
- You download that Java byte code, which can be trusted,
-
-29:37.860 --> 29:41.060
- and then you do all the compiler stuff on your machine
-
-29:41.060 --> 29:42.460
- so that you know that you trust that.
-
-29:42.460 --> 29:44.060
- Now, is that a good idea or a bad idea?
-
-29:44.060 --> 29:44.900
- It's a great idea.
-
-29:44.900 --> 29:46.240
- I mean, it's a great idea for certain problems.
-
-29:46.240 --> 29:49.540
- And I'm very much a believer that technology is itself
-
-29:49.540 --> 29:50.520
- neither good nor bad.
-
-29:50.520 --> 29:51.620
- It's how you apply it.
-
-29:52.940 --> 29:54.660
- You know, this would be a very, very bad thing
-
-29:54.660 --> 29:56.980
- for very low levels of the software stack.
-
-29:56.980 --> 30:00.300
- But in terms of solving some of these software portability
-
-30:00.300 --> 30:02.820
- and transparency, or portability problems,
-
-30:02.820 --> 30:04.240
- I think it's been really good.
-
-30:04.240 --> 30:06.600
- Now, Java ultimately didn't win out on the desktop.
-
-30:06.600 --> 30:09.420
- And like, there are good reasons for that.
-
-30:09.420 --> 30:13.220
- But it's been very successful on servers and in many places,
-
-30:13.220 --> 30:16.300
- it's been a very successful thing over decades.
-
-30:16.300 --> 30:21.300
- So what has been LLVMs and C langs improvements
-
-30:21.300 --> 30:26.300
- and optimization that throughout its history,
-
-30:28.640 --> 30:31.080
- what are some moments we had set back
-
-30:31.080 --> 30:33.280
- and really proud of what's been accomplished?
-
-30:33.280 --> 30:36.160
- Yeah, I think that the interesting thing about LLVM
-
-30:36.160 --> 30:40.120
- is not the innovations and compiler research.
-
-30:40.120 --> 30:41.900
- It has very good implementations
-
-30:41.900 --> 30:44.000
- of various important algorithms, no doubt.
-
-30:44.880 --> 30:48.280
- And a lot of really smart people have worked on it.
-
-30:48.280 --> 30:50.560
- But I think that the thing that's most profound about LLVM
-
-30:50.560 --> 30:53.840
- is that through standardization, it made things possible
-
-30:53.840 --> 30:56.200
- that otherwise wouldn't have happened, okay?
-
-30:56.200 --> 30:59.120
- And so interesting things that have happened with LLVM,
-
-30:59.120 --> 31:01.260
- for example, Sony has picked up LLVM
-
-31:01.260 --> 31:03.920
- and used it to do all the graphics compilation
-
-31:03.920 --> 31:06.080
- in their movie production pipeline.
-
-31:06.080 --> 31:07.920
- And so now they're able to have better special effects
-
-31:07.920 --> 31:09.660
- because of LLVM.
-
-31:09.660 --> 31:11.180
- That's kind of cool.
-
-31:11.180 --> 31:13.000
- That's not what it was designed for, right?
-
-31:13.000 --> 31:15.480
- But that's the sign of good infrastructure
-
-31:15.480 --> 31:18.800
- when it can be used in ways it was never designed for
-
-31:18.800 --> 31:20.960
- because it has good layering and software engineering
-
-31:20.960 --> 31:23.440
- and it's composable and things like that.
-
-31:23.440 --> 31:26.120
- Which is where, as you said, it differs from GCC.
-
-31:26.120 --> 31:28.240
- Yes, GCC is also great in various ways,
-
-31:28.240 --> 31:31.800
- but it's not as good as infrastructure technology.
-
-31:31.800 --> 31:36.160
- It's really a C compiler, or it's a Fortran compiler.
-
-31:36.160 --> 31:38.920
- It's not infrastructure in the same way.
-
-31:38.920 --> 31:41.560
- Now you can tell I don't know what I'm talking about
-
-31:41.560 --> 31:44.500
- because I keep saying C lang.
-
-31:44.500 --> 31:48.080
- You can always tell when a person has clues,
-
-31:48.080 --> 31:49.400
- by the way, to pronounce something.
-
-31:49.400 --> 31:52.580
- I don't think, have I ever used C lang?
-
-31:52.580 --> 31:54.120
- Entirely possible, have you?
-
-31:54.120 --> 31:58.200
- Well, so you've used code, it's generated probably.
-
-31:58.200 --> 32:01.760
- So C lang and LLVM are used to compile
-
-32:01.760 --> 32:05.240
- all the apps on the iPhone effectively and the OSs.
-
-32:05.240 --> 32:09.380
- It compiles Google's production server applications.
-
-32:10.560 --> 32:14.840
- It's used to build GameCube games and PlayStation 4
-
-32:14.840 --> 32:16.680
- and things like that.
-
-32:16.680 --> 32:20.120
- So as a user, I have, but just everything I've done
-
-32:20.120 --> 32:22.120
- that I experienced with Linux has been,
-
-32:22.120 --> 32:23.560
- I believe, always GCC.
-
-32:23.560 --> 32:26.520
- Yeah, I think Linux still defaults to GCC.
-
-32:26.520 --> 32:27.800
- And is there a reason for that?
-
-32:27.800 --> 32:29.440
- Or is it because, I mean, is there a reason for that?
-
-32:29.440 --> 32:32.040
- It's a combination of technical and social reasons.
-
-32:32.040 --> 32:35.960
- Many Linux developers do use C lang,
-
-32:35.960 --> 32:39.720
- but the distributions, for lots of reasons,
-
-32:40.560 --> 32:44.240
- use GCC historically, and they've not switched, yeah.
-
-32:44.240 --> 32:46.640
- Because it's just anecdotally online,
-
-32:46.640 --> 32:50.640
- it seems that LLVM has either reached the level of GCC
-
-32:50.640 --> 32:53.520
- or superseded on different features or whatever.
-
-32:53.520 --> 32:55.200
- The way I would say it is that they're so close,
-
-32:55.200 --> 32:56.040
- it doesn't matter.
-
-32:56.040 --> 32:56.860
- Yeah, exactly.
-
-32:56.860 --> 32:58.160
- Like, they're slightly better in some ways,
-
-32:58.160 --> 32:59.160
- slightly worse than otherwise,
-
-32:59.160 --> 33:03.280
- but it doesn't actually really matter anymore, that level.
-
-33:03.280 --> 33:06.280
- So in terms of optimization breakthroughs,
-
-33:06.280 --> 33:09.160
- it's just been solid incremental work.
-
-33:09.160 --> 33:12.520
- Yeah, yeah, which describes a lot of compilers.
-
-33:12.520 --> 33:15.000
- The hard thing about compilers, in my experience,
-
-33:15.000 --> 33:17.440
- is the engineering, the software engineering,
-
-33:17.440 --> 33:20.160
- making it so that you can have hundreds of people
-
-33:20.160 --> 33:23.600
- collaborating on really detailed, low level work
-
-33:23.600 --> 33:25.400
- and scaling that.
-
-33:25.400 --> 33:27.880
- And that's really hard.
-
-33:27.880 --> 33:30.680
- And that's one of the things I think LLVM has done well.
-
-33:32.160 --> 33:34.200
- And that kind of goes back to the original design goals
-
-33:34.200 --> 33:37.200
- with it to be modular and things like that.
-
-33:37.200 --> 33:38.880
- And incidentally, I don't want to take all the credit
-
-33:38.880 --> 33:39.720
- for this, right?
-
-33:39.720 --> 33:41.760
- I mean, some of the best parts about LLVM
-
-33:41.760 --> 33:43.600
- is that it was designed to be modular.
-
-33:43.600 --> 33:45.600
- And when I started, I would write, for example,
-
-33:45.600 --> 33:48.500
- a register allocator, and then somebody much smarter than me
-
-33:48.500 --> 33:50.720
- would come in and pull it out and replace it
-
-33:50.720 --> 33:52.680
- with something else that they would come up with.
-
-33:52.680 --> 33:55.200
- And because it's modular, they were able to do that.
-
-33:55.200 --> 33:58.280
- And that's one of the challenges with GCC, for example,
-
-33:58.280 --> 34:01.280
- is replacing subsystems is incredibly difficult.
-
-34:01.280 --> 34:04.680
- It can be done, but it wasn't designed for that.
-
-34:04.680 --> 34:06.080
- And that's one of the reasons that LLVM's been
-
-34:06.080 --> 34:08.760
- very successful in the research world as well.
-
-34:08.760 --> 34:12.960
- But in a community sense, Guido van Rossum, right,
-
-34:12.960 --> 34:17.960
- from Python, just retired from, what is it?
-
-34:18.480 --> 34:20.500
- Benevolent Dictator for Life, right?
-
-34:20.500 --> 34:24.720
- So in managing this community of brilliant compiler folks,
-
-34:24.720 --> 34:28.660
- is there, did it, for a time at least,
-
-34:28.660 --> 34:31.480
- fall on you to approve things?
-
-34:31.480 --> 34:34.240
- Oh yeah, so I mean, I still have something like
-
-34:34.240 --> 34:37.980
- an order of magnitude more patches in LLVM
-
-34:37.980 --> 34:42.760
- than anybody else, and many of those I wrote myself.
-
-34:42.760 --> 34:47.760
- But you still write, I mean, you're still close to the,
-
-34:47.880 --> 34:49.480
- to the, I don't know what the expression is,
-
-34:49.480 --> 34:51.000
- to the metal, you still write code.
-
-34:51.000 --> 34:52.220
- Yeah, I still write code.
-
-34:52.220 --> 34:54.240
- Not as much as I was able to in grad school,
-
-34:54.240 --> 34:56.760
- but that's an important part of my identity.
-
-34:56.760 --> 34:58.880
- But the way that LLVM has worked over time
-
-34:58.880 --> 35:01.360
- is that when I was a grad student, I could do all the work
-
-35:01.360 --> 35:04.120
- and steer everything and review every patch
-
-35:04.120 --> 35:05.800
- and make sure everything was done
-
-35:05.800 --> 35:09.040
- exactly the way my opinionated sense
-
-35:09.040 --> 35:11.760
- felt like it should be done, and that was fine.
-
-35:11.760 --> 35:14.300
- But as things scale, you can't do that, right?
-
-35:14.300 --> 35:17.100
- And so what ends up happening is LLVM
-
-35:17.100 --> 35:20.520
- has a hierarchical system of what's called code owners.
-
-35:20.520 --> 35:22.880
- These code owners are given the responsibility
-
-35:22.880 --> 35:24.880
- not to do all the work,
-
-35:24.880 --> 35:26.640
- not necessarily to review all the patches,
-
-35:26.640 --> 35:28.800
- but to make sure that the patches do get reviewed
-
-35:28.800 --> 35:30.320
- and make sure that the right thing's happening
-
-35:30.320 --> 35:32.160
- architecturally in their area.
-
-35:32.160 --> 35:36.720
- And so what you'll see is you'll see that, for example,
-
-35:36.720 --> 35:38.560
- hardware manufacturers end up owning
-
-35:38.560 --> 35:43.560
- the hardware specific parts of their hardware.
-
-35:43.600 --> 35:44.520
- That's very common.
-
-35:45.520 --> 35:47.720
- Leaders in the community that have done really good work
-
-35:47.720 --> 35:50.880
- naturally become the de facto owner of something.
-
-35:50.880 --> 35:53.400
- And then usually somebody else is like,
-
-35:53.400 --> 35:55.520
- how about we make them the official code owner?
-
-35:55.520 --> 35:58.600
- And then we'll have somebody to make sure
-
-35:58.600 --> 36:00.320
- that all the patches get reviewed in a timely manner.
-
-36:00.320 --> 36:02.080
- And then everybody's like, yes, that's obvious.
-
-36:02.080 --> 36:03.240
- And then it happens, right?
-
-36:03.240 --> 36:06.080
- And usually this is a very organic thing, which is great.
-
-36:06.080 --> 36:08.740
- And so I'm nominally the top of that stack still,
-
-36:08.740 --> 36:11.560
- but I don't spend a lot of time reviewing patches.
-
-36:11.560 --> 36:16.520
- What I do is I help negotiate a lot of the technical
-
-36:16.520 --> 36:18.040
- disagreements that end up happening
-
-36:18.040 --> 36:19.660
- and making sure that the community as a whole
-
-36:19.660 --> 36:22.040
- makes progress and is moving in the right direction
-
-36:22.040 --> 36:23.920
- and doing that.
-
-36:23.920 --> 36:28.240
- So we also started a nonprofit six years ago,
-
-36:28.240 --> 36:30.840
- seven years ago, time's gone away.
-
-36:30.840 --> 36:34.600
- And the LLVM Foundation nonprofit helps oversee
-
-36:34.600 --> 36:36.440
- all the business sides of things and make sure
-
-36:36.440 --> 36:38.800
- that the events that the LLVM community has
-
-36:38.800 --> 36:41.600
- are funded and set up and run correctly
-
-36:41.600 --> 36:42.800
- and stuff like that.
-
-36:42.800 --> 36:45.160
- But the foundation is very much stays out
-
-36:45.160 --> 36:49.060
- of the technical side of where the project is going.
-
-36:49.060 --> 36:52.160
- Right, so it sounds like a lot of it is just organic.
-
-36:53.160 --> 36:55.680
- Yeah, well, LLVM is almost 20 years old,
-
-36:55.680 --> 36:56.600
- which is hard to believe.
-
-36:56.600 --> 36:59.720
- Somebody pointed out to me recently that LLVM
-
-36:59.720 --> 37:04.600
- is now older than GCC was when LLVM started, right?
-
-37:04.600 --> 37:06.860
- So time has a way of getting away from you.
-
-37:06.860 --> 37:10.400
- But the good thing about that is it has a really robust,
-
-37:10.400 --> 37:13.520
- really amazing community of people that are
-
-37:13.520 --> 37:15.460
- in their professional lives, spread across lots
-
-37:15.460 --> 37:17.720
- of different companies, but it's a community
-
-37:17.720 --> 37:21.120
- of people that are interested in similar kinds of problems
-
-37:21.120 --> 37:23.680
- and have been working together effectively for years
-
-37:23.680 --> 37:26.460
- and have a lot of trust and respect for each other.
-
-37:26.460 --> 37:29.240
- And even if they don't always agree that we're able
-
-37:29.240 --> 37:31.200
- to find a path forward.
-
-37:31.200 --> 37:34.480
- So then in a slightly different flavor of effort,
-
-37:34.480 --> 37:38.120
- you started at Apple in 2005 with the task
-
-37:38.120 --> 37:41.800
- of making, I guess, LLVM production ready.
-
-37:41.800 --> 37:44.640
- And then eventually 2013 through 2017,
-
-37:44.640 --> 37:48.360
- leading the entire developer tools department.
-
-37:48.360 --> 37:52.960
- We're talking about LLVM, Xcode, Objective C to Swift.
-
-37:53.920 --> 37:58.580
- So in a quick overview of your time there,
-
-37:58.580 --> 37:59.600
- what were the challenges?
-
-37:59.600 --> 38:03.240
- First of all, leading such a huge group of developers,
-
-38:03.240 --> 38:06.540
- what was the big motivator, dream, mission
-
-38:06.540 --> 38:11.400
- behind creating Swift, the early birth of it
-
-38:11.400 --> 38:13.400
- from Objective C and so on, and Xcode,
-
-38:13.400 --> 38:14.240
- what are some challenges?
-
-38:14.240 --> 38:15.900
- So these are different questions.
-
-38:15.900 --> 38:19.720
- Yeah, I know, but I wanna talk about the other stuff too.
-
-38:19.720 --> 38:21.240
- I'll stay on the technical side,
-
-38:21.240 --> 38:24.480
- then we can talk about the big team pieces, if that's okay.
-
-38:24.480 --> 38:29.060
- So it's to really oversimplify many years of hard work.
-
-38:29.060 --> 38:32.440
- LLVM started, joined Apple, became a thing,
-
-38:32.440 --> 38:34.600
- became successful and became deployed.
-
-38:34.600 --> 38:35.960
- But then there's a question about
-
-38:35.960 --> 38:38.880
- how do we actually parse the source code?
-
-38:38.880 --> 38:40.320
- So LLVM is that back part,
-
-38:40.320 --> 38:42.320
- the optimizer and the code generator.
-
-38:42.320 --> 38:44.060
- And LLVM was really good for Apple
-
-38:44.060 --> 38:46.060
- as it went through a couple of harder transitions.
-
-38:46.060 --> 38:47.960
- I joined right at the time of the Intel transition,
-
-38:47.960 --> 38:51.820
- for example, and 64 bit transitions,
-
-38:51.820 --> 38:53.500
- and then the transition to ARM with the iPhone.
-
-38:53.500 --> 38:54.720
- And so LLVM was very useful
-
-38:54.720 --> 38:57.000
- for some of these kinds of things.
-
-38:57.000 --> 38:58.480
- But at the same time, there's a lot of questions
-
-38:58.480 --> 39:00.120
- around developer experience.
-
-39:00.120 --> 39:01.960
- And so if you're a programmer pounding out
-
-39:01.960 --> 39:03.460
- at the time Objective C code,
-
-39:04.480 --> 39:06.520
- the error message you get, the compile time,
-
-39:06.520 --> 39:09.760
- the turnaround cycle, the tooling and the IDE,
-
-39:09.760 --> 39:13.000
- were not great, were not as good as they could be.
-
-39:13.000 --> 39:18.000
- And so, as I occasionally do, I'm like,
-
-39:18.080 --> 39:20.720
- well, okay, how hard is it to write a C compiler?
-
-39:20.720 --> 39:22.560
- And so I'm not gonna commit to anybody,
-
-39:22.560 --> 39:25.320
- I'm not gonna tell anybody, I'm just gonna just do it
-
-39:25.320 --> 39:27.480
- nights and weekends and start working on it.
-
-39:27.480 --> 39:29.740
- And then I built up in C,
-
-39:29.740 --> 39:31.160
- there's this thing called the preprocessor,
-
-39:31.160 --> 39:33.040
- which people don't like,
-
-39:33.040 --> 39:35.480
- but it's actually really hard and complicated
-
-39:35.480 --> 39:37.700
- and includes a bunch of really weird things
-
-39:37.700 --> 39:39.280
- like trigraphs and other stuff like that
-
-39:39.280 --> 39:40.960
- that are really nasty,
-
-39:40.960 --> 39:44.080
- and it's the crux of a bunch of the performance issues
-
-39:44.080 --> 39:45.640
- in the compiler.
-
-39:45.640 --> 39:46.640
- Started working on the parser
-
-39:46.640 --> 39:47.800
- and kind of got to the point where I'm like,
-
-39:47.800 --> 39:49.880
- ah, you know what, we could actually do this.
-
-39:49.880 --> 39:51.460
- Everybody's saying that this is impossible to do,
-
-39:51.460 --> 39:53.960
- but it's actually just hard, it's not impossible.
-
-39:53.960 --> 39:57.560
- And eventually told my manager about it,
-
-39:57.560 --> 39:59.220
- and he's like, oh, wow, this is great,
-
-39:59.220 --> 40:00.360
- we do need to solve this problem.
-
-40:00.360 --> 40:02.560
- Oh, this is great, we can get you one other person
-
-40:02.560 --> 40:04.440
- to work with you on this, you know?
-
-40:04.440 --> 40:08.360
- And slowly a team is formed and it starts taking off.
-
-40:08.360 --> 40:12.040
- And C++, for example, huge, complicated language.
-
-40:12.040 --> 40:14.360
- People always assume that it's impossible to implement
-
-40:14.360 --> 40:16.260
- and it's very nearly impossible,
-
-40:16.260 --> 40:18.720
- but it's just really, really hard.
-
-40:18.720 --> 40:20.840
- And the way to get there is to build it
-
-40:20.840 --> 40:22.480
- one piece at a time incrementally.
-
-40:22.480 --> 40:26.440
- And that was only possible because we were lucky
-
-40:26.440 --> 40:28.160
- to hire some really exceptional engineers
-
-40:28.160 --> 40:30.380
- that knew various parts of it very well
-
-40:30.380 --> 40:32.680
- and could do great things.
-
-40:32.680 --> 40:34.440
- Swift was kind of a similar thing.
-
-40:34.440 --> 40:39.160
- So Swift came from, we were just finishing off
-
-40:39.160 --> 40:42.600
- the first version of C++ support in Clang.
-
-40:42.600 --> 40:47.260
- And C++ is a very formidable and very important language,
-
-40:47.260 --> 40:49.280
- but it's also ugly in lots of ways.
-
-40:49.280 --> 40:52.320
- And you can't influence C++ without thinking
-
-40:52.320 --> 40:54.380
- there has to be a better thing, right?
-
-40:54.380 --> 40:56.120
- And so I started working on Swift, again,
-
-40:56.120 --> 40:58.560
- with no hope or ambition that would go anywhere,
-
-40:58.560 --> 41:00.800
- just let's see what could be done,
-
-41:00.800 --> 41:02.620
- let's play around with this thing.
-
-41:02.620 --> 41:06.700
- It was me in my spare time, not telling anybody about it,
-
-41:06.700 --> 41:09.420
- kind of a thing, and it made some good progress.
-
-41:09.420 --> 41:11.260
- I'm like, actually, it would make sense to do this.
-
-41:11.260 --> 41:14.800
- At the same time, I started talking with the senior VP
-
-41:14.800 --> 41:17.720
- of software at the time, a guy named Bertrand Serlet.
-
-41:17.720 --> 41:19.280
- And Bertrand was very encouraging.
-
-41:19.280 --> 41:22.080
- He was like, well, let's have fun, let's talk about this.
-
-41:22.080 --> 41:23.440
- And he was a little bit of a language guy,
-
-41:23.440 --> 41:26.160
- and so he helped guide some of the early work
-
-41:26.160 --> 41:30.420
- and encouraged me and got things off the ground.
-
-41:30.420 --> 41:34.280
- And eventually told my manager and told other people,
-
-41:34.280 --> 41:38.800
- and it started making progress.
-
-41:38.800 --> 41:40.960
- The complicating thing with Swift
-
-41:40.960 --> 41:43.880
- was that the idea of doing a new language
-
-41:43.880 --> 41:47.840
- was not obvious to anybody, including myself.
-
-41:47.840 --> 41:50.240
- And the tone at the time was that the iPhone
-
-41:50.240 --> 41:53.440
- was successful because of Objective C.
-
-41:53.440 --> 41:54.440
- Oh, interesting.
-
-41:54.440 --> 41:57.160
- Not despite of or just because of.
-
-41:57.160 --> 42:01.160
- And you have to understand that at the time,
-
-42:01.160 --> 42:05.400
- Apple was hiring software people that loved Objective C.
-
-42:05.400 --> 42:07.960
- And it wasn't that they came despite Objective C.
-
-42:07.960 --> 42:10.240
- They loved Objective C, and that's why they got hired.
-
-42:10.240 --> 42:13.080
- And so you had a software team that the leadership,
-
-42:13.080 --> 42:15.200
- in many cases, went all the way back to Next,
-
-42:15.200 --> 42:19.400
- where Objective C really became real.
-
-42:19.400 --> 42:23.240
- And so they, quote unquote, grew up writing Objective C.
-
-42:23.240 --> 42:25.720
- And many of the individual engineers
-
-42:25.720 --> 42:28.360
- all were hired because they loved Objective C.
-
-42:28.360 --> 42:30.560
- And so this notion of, OK, let's do new language
-
-42:30.560 --> 42:34.120
- was kind of heretical in many ways.
-
-42:34.120 --> 42:36.960
- Meanwhile, my sense was that the outside community wasn't really
-
-42:36.960 --> 42:38.560
- in love with Objective C. Some people were,
-
-42:38.560 --> 42:40.360
- and some of the most outspoken people were.
-
-42:40.360 --> 42:42.620
- But other people were hitting challenges
-
-42:42.620 --> 42:44.760
- because it has very sharp corners
-
-42:44.760 --> 42:46.840
- and it's difficult to learn.
-
-42:46.840 --> 42:50.160
- And so one of the challenges of making Swift happen that
-
-42:50.160 --> 42:57.720
- was totally non technical is the social part of what do we do?
-
-42:57.720 --> 43:00.320
- If we do a new language, which at Apple, many things
-
-43:00.320 --> 43:02.240
- happen that don't ship.
-
-43:02.240 --> 43:05.560
- So if we ship it, what is the metrics of success?
-
-43:05.560 --> 43:06.400
- Why would we do this?
-
-43:06.400 --> 43:08.060
- Why wouldn't we make Objective C better?
-
-43:08.060 --> 43:10.160
- If Objective C has problems, let's file off
-
-43:10.160 --> 43:12.160
- those rough corners and edges.
-
-43:12.160 --> 43:15.640
- And one of the major things that became the reason to do this
-
-43:15.640 --> 43:18.960
- was this notion of safety, memory safety.
-
-43:18.960 --> 43:23.240
- And the way Objective C works is that a lot of the object system
-
-43:23.240 --> 43:27.560
- and everything else is built on top of pointers in C.
-
-43:27.560 --> 43:29.960
- Objective C is an extension on top of C.
-
-43:29.960 --> 43:32.680
- And so pointers are unsafe.
-
-43:32.680 --> 43:34.640
- And if you get rid of the pointers,
-
-43:34.640 --> 43:36.480
- it's not Objective C anymore.
-
-43:36.480 --> 43:39.080
- And so fundamentally, that was an issue
-
-43:39.080 --> 43:42.200
- that you could not fix safety or memory safety
-
-43:42.200 --> 43:45.640
- without fundamentally changing the language.
-
-43:45.640 --> 43:49.920
- And so once we got through that part of the mental process
-
-43:49.920 --> 43:53.200
- and the thought process, it became a design process
-
-43:53.200 --> 43:55.400
- of saying, OK, well, if we're going to do something new,
-
-43:55.400 --> 43:56.280
- what is good?
-
-43:56.280 --> 43:57.400
- How do we think about this?
-
-43:57.400 --> 43:58.200
- And what do we like?
-
-43:58.200 --> 44:00.040
- And what are we looking for?
-
-44:00.040 --> 44:02.440
- And that was a very different phase of it.
-
-44:02.440 --> 44:05.960
- So what are some design choices early on in Swift?
-
-44:05.960 --> 44:10.120
- Like we're talking about braces, are you
-
-44:10.120 --> 44:13.240
- making a typed language or not, all those kinds of things.
-
-44:13.240 --> 44:16.040
- Yeah, so some of those were obvious given the context.
-
-44:16.040 --> 44:17.800
- So a typed language, for example,
-
-44:17.800 --> 44:19.200
- Objective C is a typed language.
-
-44:19.200 --> 44:22.480
- And going with an untyped language
-
-44:22.480 --> 44:24.320
- wasn't really seriously considered.
-
-44:24.320 --> 44:26.000
- We wanted the performance, and we
-
-44:26.000 --> 44:27.680
- wanted refactoring tools and other things
-
-44:27.680 --> 44:29.600
- like that that go with typed languages.
-
-44:29.600 --> 44:31.440
- Quick, dumb question.
-
-44:31.440 --> 44:34.600
- Was it obvious, I think this would be a dumb question,
-
-44:34.600 --> 44:36.360
- but was it obvious that the language
-
-44:36.360 --> 44:40.120
- has to be a compiled language?
-
-44:40.120 --> 44:42.080
- Yes, that's not a dumb question.
-
-44:42.080 --> 44:44.520
- Earlier, I think late 90s, Apple had seriously
-
-44:44.520 --> 44:49.000
- considered moving its development experience to Java.
-
-44:49.000 --> 44:53.160
- But Swift started in 2010, which was several years
-
-44:53.160 --> 44:53.880
- after the iPhone.
-
-44:53.880 --> 44:55.380
- It was when the iPhone was definitely
-
-44:55.380 --> 44:56.640
- on an upward trajectory.
-
-44:56.640 --> 44:58.760
- And the iPhone was still extremely,
-
-44:58.760 --> 45:01.800
- and is still a bit memory constrained.
-
-45:01.800 --> 45:04.440
- And so being able to compile the code
-
-45:04.440 --> 45:08.160
- and then ship it and then having standalone code that
-
-45:08.160 --> 45:11.320
- is not JIT compiled is a very big deal
-
-45:11.320 --> 45:15.200
- and is very much part of the Apple value system.
-
-45:15.200 --> 45:17.480
- Now, JavaScript's also a thing.
-
-45:17.480 --> 45:19.360
- I mean, it's not that this is exclusive,
-
-45:19.360 --> 45:21.640
- and technologies are good depending
-
-45:21.640 --> 45:23.880
- on how they're applied.
-
-45:23.880 --> 45:26.600
- But in the design of Swift, saying,
-
-45:26.600 --> 45:28.320
- how can we make Objective C better?
-
-45:28.320 --> 45:29.760
- Objective C is statically compiled,
-
-45:29.760 --> 45:32.520
- and that was the contiguous, natural thing to do.
-
-45:32.520 --> 45:35.360
- Just skip ahead a little bit, and we'll go right back.
-
-45:35.360 --> 45:40.040
- Just as a question, as you think about today in 2019
-
-45:40.040 --> 45:42.400
- in your work at Google, TensorFlow and so on,
-
-45:42.400 --> 45:48.600
- is, again, compilations, static compilation still
-
-45:48.600 --> 45:49.460
- the right thing?
-
-45:49.460 --> 45:52.000
- Yeah, so the funny thing after working
-
-45:52.000 --> 45:55.880
- on compilers for a really long time is that,
-
-45:55.880 --> 45:59.040
- and this is one of the things that LLVM has helped with,
-
-45:59.040 --> 46:01.440
- is that I don't look at compilations
-
-46:01.440 --> 46:05.240
- being static or dynamic or interpreted or not.
-
-46:05.240 --> 46:07.680
- This is a spectrum.
-
-46:07.680 --> 46:09.140
- And one of the cool things about Swift
-
-46:09.140 --> 46:12.160
- is that Swift is not just statically compiled.
-
-46:12.160 --> 46:14.080
- It's actually dynamically compiled as well,
-
-46:14.080 --> 46:15.320
- and it can also be interpreted.
-
-46:15.320 --> 46:17.440
- Though, nobody's actually done that.
-
-46:17.440 --> 46:20.400
- And so what ends up happening when
-
-46:20.400 --> 46:24.080
- you use Swift in a workbook, for example in Colab or in Jupyter,
-
-46:24.080 --> 46:26.360
- is it's actually dynamically compiling the statements
-
-46:26.360 --> 46:28.160
- as you execute them.
-
-46:28.160 --> 46:32.840
- And so this gets back to the software engineering problems,
-
-46:32.840 --> 46:34.960
- where if you layer the stack properly,
-
-46:34.960 --> 46:37.320
- you can actually completely change
-
-46:37.320 --> 46:39.360
- how and when things get compiled because you
-
-46:39.360 --> 46:41.120
- have the right abstractions there.
-
-46:41.120 --> 46:44.800
- And so the way that a Colab workbook works with Swift
-
-46:44.800 --> 46:47.720
- is that when you start typing into it,
-
-46:47.720 --> 46:50.280
- it creates a process, a Unix process.
-
-46:50.280 --> 46:52.160
- And then each line of code you type in,
-
-46:52.160 --> 46:56.120
- it compiles it through the Swift compiler, the front end part,
-
-46:56.120 --> 46:58.360
- and then sends it through the optimizer,
-
-46:58.360 --> 47:01.120
- JIT compiles machine code, and then
-
-47:01.120 --> 47:03.800
- injects it into that process.
-
-47:03.800 --> 47:05.400
- And so as you're typing new stuff,
-
-47:05.400 --> 47:09.360
- it's like squirting in new code and overwriting and replacing
-
-47:09.360 --> 47:11.200
- and updating code in place.
-
-47:11.200 --> 47:13.680
- And the fact that it can do this is not an accident.
-
-47:13.680 --> 47:15.560
- Swift was designed for this.
-
-47:15.560 --> 47:18.120
- But it's an important part of how the language was set up
-
-47:18.120 --> 47:21.320
- and how it's layered, and this is a nonobvious piece.
-
-47:21.320 --> 47:23.160
- And one of the things with Swift that
-
-47:23.160 --> 47:25.880
- was, for me, a very strong design point
-
-47:25.880 --> 47:29.640
- is to make it so that you can learn it very quickly.
-
-47:29.640 --> 47:31.880
- And so from a language design perspective,
-
-47:31.880 --> 47:33.340
- the thing that I always come back to
-
-47:33.340 --> 47:36.440
- is this UI principle of progressive disclosure
-
-47:36.440 --> 47:37.960
- of complexity.
-
-47:37.960 --> 47:41.680
- And so in Swift, you can start by saying print, quote,
-
-47:41.680 --> 47:44.040
- hello world, quote.
-
-47:44.040 --> 47:47.160
- And there's no slash n, just like Python, one line of code,
-
-47:47.160 --> 47:51.520
- no main, no header files, no public static class void,
-
-47:51.520 --> 47:55.640
- blah, blah, blah, string like Java has, one line of code.
-
-47:55.640 --> 47:58.400
- And you can teach that, and it works great.
-
-47:58.400 --> 48:00.400
- Then you can say, well, let's introduce variables.
-
-48:00.400 --> 48:02.400
- And so you can declare a variable with var.
-
-48:02.400 --> 48:03.780
- So var x equals 4.
-
-48:03.780 --> 48:04.700
- What is a variable?
-
-48:04.700 --> 48:06.280
- You can use x, x plus 1.
-
-48:06.280 --> 48:07.600
- This is what it means.
-
-48:07.600 --> 48:09.520
- Then you can say, well, how about control flow?
-
-48:09.520 --> 48:10.860
- Well, this is what an if statement is.
-
-48:10.860 --> 48:12.280
- This is what a for statement is.
-
-48:12.280 --> 48:15.280
- This is what a while statement is.
-
-48:15.280 --> 48:17.280
- Then you can say, let's introduce functions.
-
-48:17.280 --> 48:20.020
- And many languages like Python have
-
-48:20.020 --> 48:22.820
- had this kind of notion of let's introduce small things,
-
-48:22.820 --> 48:24.400
- and then you can add complexity.
-
-48:24.400 --> 48:25.760
- Then you can introduce classes.
-
-48:25.760 --> 48:28.040
- And then you can add generics, in the case of Swift.
-
-48:28.040 --> 48:29.520
- And then you can build in modules
-
-48:29.520 --> 48:32.200
- and build out in terms of the things that you're expressing.
-
-48:32.200 --> 48:35.800
- But this is not very typical for compiled languages.
-
-48:35.800 --> 48:38.000
- And so this was a very strong design point,
-
-48:38.000 --> 48:40.960
- and one of the reasons that Swift, in general,
-
-48:40.960 --> 48:43.480
- is designed with this factoring of complexity in mind
-
-48:43.480 --> 48:46.440
- so that the language can express powerful things.
-
-48:46.440 --> 48:49.280
- You can write firmware in Swift if you want to.
-
-48:49.280 --> 48:51.900
- But it has a very high level feel,
-
-48:51.900 --> 48:55.200
- which is really this perfect blend, because often you
-
-48:55.200 --> 48:57.520
- have very advanced library writers that
-
-48:57.520 --> 49:00.520
- want to be able to use the nitty gritty details.
-
-49:00.520 --> 49:02.960
- But then other people just want to use the libraries
-
-49:02.960 --> 49:04.880
- and work at a higher abstraction level.
-
-49:04.880 --> 49:07.240
- It's kind of cool that I saw that you can just
-
-49:07.240 --> 49:09.240
- interoperability.
-
-49:09.240 --> 49:11.320
- I don't think I pronounced that word enough.
-
-49:11.320 --> 49:14.960
- But you can just drag in Python.
-
-49:14.960 --> 49:16.000
- It's just strange.
-
-49:16.000 --> 49:19.640
- You can import, like I saw this in the demo.
-
-49:19.640 --> 49:21.280
- How do you make that happen?
-
-49:21.280 --> 49:23.120
- What's up with that?
-
-49:23.120 --> 49:25.560
- Is that as easy as it looks, or is it?
-
-49:25.560 --> 49:27.000
- Yes, as easy as it looks.
-
-49:27.000 --> 49:29.600
- That's not a stage magic hack or anything like that.
-
-49:29.600 --> 49:31.400
- I don't mean from the user perspective.
-
-49:31.400 --> 49:34.120
- I mean from the implementation perspective to make it happen.
-
-49:34.120 --> 49:37.000
- So it's easy once all the pieces are in place.
-
-49:37.000 --> 49:39.280
- The way it works, so if you think about a dynamically typed
-
-49:39.280 --> 49:41.480
- language like Python, you can think about it
-
-49:41.480 --> 49:42.360
- in two different ways.
-
-49:42.360 --> 49:45.800
- You can say it has no types, which
-
-49:45.800 --> 49:47.480
- is what most people would say.
-
-49:47.480 --> 49:50.400
- Or you can say it has one type.
-
-49:50.400 --> 49:53.320
- And you can say it has one type, and it's the Python object.
-
-49:53.320 --> 49:55.000
- And the Python object gets passed around.
-
-49:55.000 --> 49:58.200
- And because there's only one type, it's implicit.
-
-49:58.200 --> 50:00.880
- And so what happens with Swift and Python talking
-
-50:00.880 --> 50:02.760
- to each other, Swift has lots of types.
-
-50:02.760 --> 50:05.840
- It has arrays, and it has strings, and all classes,
-
-50:05.840 --> 50:07.000
- and that kind of stuff.
-
-50:07.000 --> 50:11.120
- But it now has a Python object type.
-
-50:11.120 --> 50:12.720
- So there is one Python object type.
-
-50:12.720 --> 50:16.440
- And so when you say import NumPy, what you get
-
-50:16.440 --> 50:19.840
- is a Python object, which is the NumPy module.
-
-50:19.840 --> 50:21.960
- And then you say np.array.
-
-50:21.960 --> 50:24.960
- It says, OK, hey, Python object, I have no idea what you are.
-
-50:24.960 --> 50:27.280
- Give me your array member.
-
-50:27.280 --> 50:27.960
- OK, cool.
-
-50:27.960 --> 50:31.160
- And it just uses dynamic stuff, talks to the Python interpreter,
-
-50:31.160 --> 50:33.680
- and says, hey, Python, what's the.array member
-
-50:33.680 --> 50:35.720
- in that Python object?
-
-50:35.720 --> 50:37.400
- It gives you back another Python object.
-
-50:37.400 --> 50:40.040
- And now you say parentheses for the call and the arguments
-
-50:40.040 --> 50:40.920
- you're going to pass.
-
-50:40.920 --> 50:43.520
- And so then it says, hey, a Python object
-
-50:43.520 --> 50:47.840
- that is the result of np.array, call with these arguments.
-
-50:47.840 --> 50:50.320
- Again, calling into the Python interpreter to do that work.
-
-50:50.320 --> 50:53.680
- And so right now, this is all really simple.
-
-50:53.680 --> 50:55.960
- And if you dive into the code, what you'll see
-
-50:55.960 --> 50:58.440
- is that the Python module in Swift
-
-50:58.440 --> 51:01.360
- is something like 1,200 lines of code or something.
-
-51:01.360 --> 51:02.400
- It's written in pure Swift.
-
-51:02.400 --> 51:03.560
- It's super simple.
-
-51:03.560 --> 51:06.560
- And it's built on top of the C interoperability
-
-51:06.560 --> 51:09.520
- because it just talks to the Python interpreter.
-
-51:09.520 --> 51:11.080
- But making that possible required
-
-51:11.080 --> 51:13.480
- us to add two major language features to Swift
-
-51:13.480 --> 51:15.400
- to be able to express these dynamic calls
-
-51:15.400 --> 51:17.240
- and the dynamic member lookups.
-
-51:17.240 --> 51:19.480
- And so what we've done over the last year
-
-51:19.480 --> 51:23.960
- is we've proposed, implement, standardized, and contributed
-
-51:23.960 --> 51:26.160
- new language features to the Swift language
-
-51:26.160 --> 51:29.560
- in order to make it so it is really trivial.
-
-51:29.560 --> 51:31.320
- And this is one of the things about Swift
-
-51:31.320 --> 51:35.000
- that is critical to the Swift for TensorFlow work, which
-
-51:35.000 --> 51:37.200
- is that we can actually add new language features.
-
-51:37.200 --> 51:39.160
- And the bar for adding those is high,
-
-51:39.160 --> 51:42.280
- but it's what makes it possible.
-
-51:42.280 --> 51:45.240
- So you're now at Google doing incredible work
-
-51:45.240 --> 51:47.680
- on several things, including TensorFlow.
-
-51:47.680 --> 51:53.080
- So TensorFlow 2.0 or whatever leading up to 2.0 has,
-
-51:53.080 --> 51:56.840
- by default, in 2.0, has eager execution.
-
-51:56.840 --> 52:00.520
- And yet, in order to make code optimized for GPU or TPU
-
-52:00.520 --> 52:04.120
- or some of these systems, computation
-
-52:04.120 --> 52:06.000
- needs to be converted to a graph.
-
-52:06.000 --> 52:07.440
- So what's that process like?
-
-52:07.440 --> 52:08.960
- What are the challenges there?
-
-52:08.960 --> 52:11.720
- Yeah, so I am tangentially involved in this.
-
-52:11.720 --> 52:15.280
- But the way that it works with Autograph
-
-52:15.280 --> 52:21.600
- is that you mark your function with a decorator.
-
-52:21.600 --> 52:24.280
- And when Python calls it, that decorator is invoked.
-
-52:24.280 --> 52:28.240
- And then it says, before I call this function,
-
-52:28.240 --> 52:29.480
- you can transform it.
-
-52:29.480 --> 52:32.400
- And so the way Autograph works is, as far as I understand,
-
-52:32.400 --> 52:34.440
- is it actually uses the Python parser
-
-52:34.440 --> 52:37.160
- to go parse that, turn it into a syntax tree,
-
-52:37.160 --> 52:39.400
- and now apply compiler techniques to, again,
-
-52:39.400 --> 52:42.320
- transform this down into TensorFlow graphs.
-
-52:42.320 --> 52:44.920
- And so you can think of it as saying, hey,
-
-52:44.920 --> 52:45.880
- I have an if statement.
-
-52:45.880 --> 52:48.360
- I'm going to create an if node in the graph,
-
-52:48.360 --> 52:51.080
- like you say tf.cond.
-
-52:51.080 --> 52:53.040
- You have a multiply.
-
-52:53.040 --> 52:55.320
- Well, I'll turn that into a multiply node in the graph.
-
-52:55.320 --> 52:57.760
- And it becomes this tree transformation.
-
-52:57.760 --> 53:00.480
- So where does the Swift for TensorFlow
-
-53:00.480 --> 53:04.960
- come in, which is parallels?
-
-53:04.960 --> 53:06.960
- For one, Swift is an interface.
-
-53:06.960 --> 53:09.200
- Like, Python is an interface to TensorFlow.
-
-53:09.200 --> 53:11.760
- But it seems like there's a lot more going on in just
-
-53:11.760 --> 53:13.120
- a different language interface.
-
-53:13.120 --> 53:15.960
- There's optimization methodology.
-
-53:15.960 --> 53:17.920
- So the TensorFlow world has a couple
-
-53:17.920 --> 53:21.240
- of different what I'd call front end technologies.
-
-53:21.240 --> 53:25.240
- And so Swift and Python and Go and Rust and Julia
-
-53:25.240 --> 53:29.320
- and all these things share the TensorFlow graphs
-
-53:29.320 --> 53:32.760
- and all the runtime and everything that's later.
-
-53:32.760 --> 53:36.640
- And so Swift for TensorFlow is merely another front end
-
-53:36.640 --> 53:40.640
- for TensorFlow, just like any of these other systems are.
-
-53:40.640 --> 53:43.080
- There's a major difference between, I would say,
-
-53:43.080 --> 53:44.600
- three camps of technologies here.
-
-53:44.600 --> 53:46.880
- There's Python, which is a special case,
-
-53:46.880 --> 53:49.160
- because the vast majority of the community effort
-
-53:49.160 --> 53:51.120
- is going to the Python interface.
-
-53:51.120 --> 53:52.920
- And Python has its own approaches
-
-53:52.920 --> 53:54.480
- for automatic differentiation.
-
-53:54.480 --> 53:58.160
- It has its own APIs and all this kind of stuff.
-
-53:58.160 --> 54:00.320
- There's Swift, which I'll talk about in a second.
-
-54:00.320 --> 54:02.040
- And then there's kind of everything else.
-
-54:02.040 --> 54:05.400
- And so the everything else are effectively language bindings.
-
-54:05.400 --> 54:07.960
- So they call into the TensorFlow runtime,
-
-54:07.960 --> 54:10.920
- but they usually don't have automatic differentiation
-
-54:10.920 --> 54:14.560
- or they usually don't provide anything other than APIs
-
-54:14.560 --> 54:16.440
- that call the C APIs in TensorFlow.
-
-54:16.440 --> 54:18.360
- And so they're kind of wrappers for that.
-
-54:18.360 --> 54:19.840
- Swift is really kind of special.
-
-54:19.840 --> 54:22.760
- And it's a very different approach.
-
-54:22.760 --> 54:25.360
- Swift for TensorFlow, that is, is a very different approach.
-
-54:25.360 --> 54:26.880
- Because there we're saying, let's
-
-54:26.880 --> 54:28.400
- look at all the problems that need
-
-54:28.400 --> 54:34.080
- to be solved in the full stack of the TensorFlow compilation
-
-54:34.080 --> 54:35.680
- process, if you think about it that way.
-
-54:35.680 --> 54:38.200
- Because TensorFlow is fundamentally a compiler.
-
-54:38.200 --> 54:42.760
- It takes models, and then it makes them go fast on hardware.
-
-54:42.760 --> 54:43.880
- That's what a compiler does.
-
-54:43.880 --> 54:47.560
- And it has a front end, it has an optimizer,
-
-54:47.560 --> 54:49.320
- and it has many back ends.
-
-54:49.320 --> 54:51.680
- And so if you think about it the right way,
-
-54:51.680 --> 54:54.800
- or if you look at it in a particular way,
-
-54:54.800 --> 54:55.560
- it is a compiler.
-
-54:59.280 --> 55:02.120
- And so Swift is merely another front end.
-
-55:02.120 --> 55:05.560
- But it's saying, and the design principle is saying,
-
-55:05.560 --> 55:08.240
- let's look at all the problems that we face as machine
-
-55:08.240 --> 55:11.320
- learning practitioners and what is the best possible way we
-
-55:11.320 --> 55:13.840
- can do that, given the fact that we can change literally
-
-55:13.840 --> 55:15.920
- anything in this entire stack.
-
-55:15.920 --> 55:18.440
- And Python, for example, where the vast majority
-
-55:18.440 --> 55:22.600
- of the engineering and effort has gone into,
-
-55:22.600 --> 55:25.000
- is constrained by being the best possible thing you
-
-55:25.000 --> 55:27.320
- can do with a Python library.
-
-55:27.320 --> 55:29.320
- There are no Python language features
-
-55:29.320 --> 55:31.040
- that are added because of machine learning
-
-55:31.040 --> 55:32.600
- that I'm aware of.
-
-55:32.600 --> 55:34.640
- They added a matrix multiplication operator
-
-55:34.640 --> 55:38.320
- with that, but that's as close as you get.
-
-55:38.320 --> 55:41.460
- And so with Swift, it's hard, but you
-
-55:41.460 --> 55:43.800
- can add language features to the language.
-
-55:43.800 --> 55:46.040
- And there's a community process for that.
-
-55:46.040 --> 55:48.200
- And so we look at these things and say, well,
-
-55:48.200 --> 55:49.720
- what is the right division of labor
-
-55:49.720 --> 55:52.000
- between the human programmer and the compiler?
-
-55:52.000 --> 55:55.280
- And Swift has a number of things that shift that balance.
-
-55:55.280 --> 56:00.560
- So because it has a type system, for example,
-
-56:00.560 --> 56:02.680
- that makes certain things possible for analysis
-
-56:02.680 --> 56:05.560
- of the code, and the compiler can automatically
-
-56:05.560 --> 56:08.880
- build graphs for you without you thinking about them.
-
-56:08.880 --> 56:10.520
- That's a big deal for a programmer.
-
-56:10.520 --> 56:11.680
- You just get free performance.
-
-56:11.680 --> 56:14.400
- You get clustering and fusion and optimization,
-
-56:14.400 --> 56:17.040
- things like that, without you as a programmer
-
-56:17.040 --> 56:20.080
- having to manually do it because the compiler can do it for you.
-
-56:20.080 --> 56:22.240
- Automatic differentiation is another big deal.
-
-56:22.240 --> 56:25.960
- And I think one of the key contributions of the Swift
-
-56:25.960 --> 56:29.640
- TensorFlow project is that there's
-
-56:29.640 --> 56:32.120
- this entire body of work on automatic differentiation
-
-56:32.120 --> 56:34.120
- that dates back to the Fortran days.
-
-56:34.120 --> 56:36.400
- People doing a tremendous amount of numerical computing
-
-56:36.400 --> 56:39.360
- in Fortran used to write these what they call source
-
-56:39.360 --> 56:43.280
- to source translators, where you take a bunch of code,
-
-56:43.280 --> 56:46.640
- shove it into a mini compiler, and it would push out
-
-56:46.640 --> 56:48.080
- more Fortran code.
-
-56:48.080 --> 56:50.240
- But it would generate the backwards passes
-
-56:50.240 --> 56:53.000
- for your functions for you, the derivatives.
-
-56:53.000 --> 56:57.840
- And so in that work in the 70s, a tremendous number
-
-56:57.840 --> 57:01.160
- of optimizations, a tremendous number of techniques
-
-57:01.160 --> 57:02.920
- for fixing numerical instability,
-
-57:02.920 --> 57:05.080
- and other kinds of problems were developed.
-
-57:05.080 --> 57:07.600
- But they're very difficult to port into a world
-
-57:07.600 --> 57:11.280
- where, in eager execution, you get an op by op at a time.
-
-57:11.280 --> 57:13.280
- You need to be able to look at an entire function
-
-57:13.280 --> 57:15.720
- and be able to reason about what's going on.
-
-57:15.720 --> 57:18.720
- And so when you have a language integrated automatic
-
-57:18.720 --> 57:20.520
- differentiation, which is one of the things
-
-57:20.520 --> 57:22.760
- that the Swift project is focusing on,
-
-57:22.760 --> 57:24.680
- you can open all these techniques
-
-57:24.680 --> 57:28.640
- and reuse them in familiar ways.
-
-57:28.640 --> 57:30.120
- But the language integration piece
-
-57:30.120 --> 57:33.240
- has a bunch of design room in it, and it's also complicated.
-
-57:33.240 --> 57:35.680
- The other piece of the puzzle here that's kind of interesting
-
-57:35.680 --> 57:37.560
- is TPUs at Google.
-
-57:37.560 --> 57:40.200
- So we're in a new world with deep learning.
-
-57:40.200 --> 57:42.960
- It constantly is changing, and I imagine,
-
-57:42.960 --> 57:46.360
- without disclosing anything, I imagine
-
-57:46.360 --> 57:48.400
- you're still innovating on the TPU front, too.
-
-57:48.400 --> 57:49.040
- Indeed.
-
-57:49.040 --> 57:53.560
- So how much interplay is there between software and hardware
-
-57:53.560 --> 57:55.240
- in trying to figure out how to together move
-
-57:55.240 --> 57:56.680
- towards an optimized solution?
-
-57:56.680 --> 57:57.760
- There's an incredible amount.
-
-57:57.760 --> 57:59.480
- So we're on our third generation of TPUs,
-
-57:59.480 --> 58:04.640
- which are now 100 petaflops in a very large liquid cooled box,
-
-58:04.640 --> 58:07.720
- virtual box with no cover.
-
-58:07.720 --> 58:11.240
- And as you might imagine, we're not out of ideas yet.
-
-58:11.240 --> 58:14.360
- The great thing about TPUs is that they're
-
-58:14.360 --> 58:17.520
- a perfect example of hardware software co design.
-
-58:17.520 --> 58:19.800
- And so it's about saying, what hardware
-
-58:19.800 --> 58:23.240
- do we build to solve certain classes of machine learning
-
-58:23.240 --> 58:23.840
- problems?
-
-58:23.840 --> 58:26.480
- Well, the algorithms are changing.
-
-58:26.480 --> 58:30.360
- The hardware takes some cases years to produce.
-
-58:30.360 --> 58:32.760
- And so you have to make bets and decide
-
-58:32.760 --> 58:36.520
- what is going to happen and what is the best way to spend
-
-58:36.520 --> 58:39.920
- the transistors to get the maximum performance per watt
-
-58:39.920 --> 58:44.000
- or area per cost or whatever it is that you're optimizing for.
-
-58:44.000 --> 58:46.560
- And so one of the amazing things about TPUs
-
-58:46.560 --> 58:49.960
- is this numeric format called bfloat16.
-
-58:49.960 --> 58:54.120
- bfloat16 is a compressed 16 bit floating point format,
-
-58:54.120 --> 58:55.960
- but it puts the bits in different places.
-
-58:55.960 --> 58:58.960
- And in numeric terms, it has a smaller mantissa
-
-58:58.960 --> 59:00.400
- and a larger exponent.
-
-59:00.400 --> 59:02.960
- That means that it's less precise,
-
-59:02.960 --> 59:05.680
- but it can represent larger ranges of values,
-
-59:05.680 --> 59:07.280
- which in the machine learning context
-
-59:07.280 --> 59:09.960
- is really important and useful because sometimes you
-
-59:09.960 --> 59:13.920
- have very small gradients you want to accumulate
-
-59:13.920 --> 59:17.480
- and very, very small numbers that
-
-59:17.480 --> 59:20.520
- are important to move things as you're learning.
-
-59:20.520 --> 59:23.160
- But sometimes you have very large magnitude numbers as well.
-
-59:23.160 --> 59:26.880
- And bfloat16 is not as precise.
-
-59:26.880 --> 59:28.040
- The mantissa is small.
-
-59:28.040 --> 59:30.360
- But it turns out the machine learning algorithms actually
-
-59:30.360 --> 59:31.520
- want to generalize.
-
-59:31.520 --> 59:34.320
- And so there's theories that this actually
-
-59:34.320 --> 59:36.440
- increases the ability for the network
-
-59:36.440 --> 59:37.960
- to generalize across data sets.
-
-59:37.960 --> 59:41.160
- And regardless of whether it's good or bad,
-
-59:41.160 --> 59:43.680
- it's much cheaper at the hardware level to implement
-
-59:43.680 --> 59:48.080
- because the area and time of a multiplier
-
-59:48.080 --> 59:50.840
- is n squared in the number of bits in the mantissa,
-
-59:50.840 --> 59:53.320
- but it's linear with size of the exponent.
-
-59:53.320 --> 59:55.400
- And you're connected to both efforts
-
-59:55.400 --> 59:57.160
- here both on the hardware and the software side?
-
-59:57.160 --> 59:58.880
- Yeah, and so that was a breakthrough
-
-59:58.880 --> 1:00:01.440
- coming from the research side and people
-
-1:00:01.440 --> 1:00:06.000
- working on optimizing network transport of weights
-
-1:00:06.000 --> 1:00:08.240
- across the network originally and trying
-
-1:00:08.240 --> 1:00:10.160
- to find ways to compress that.
-
-1:00:10.160 --> 1:00:12.120
- But then it got burned into silicon.
-
-1:00:12.120 --> 1:00:14.560
- And it's a key part of what makes TPU performance
-
-1:00:14.560 --> 1:00:17.880
- so amazing and great.
-
-1:00:17.880 --> 1:00:20.680
- Now, TPUs have many different aspects that are important.
-
-1:00:20.680 --> 1:00:25.080
- But the co design between the low level compiler bits
-
-1:00:25.080 --> 1:00:27.360
- and the software bits and the algorithms
-
-1:00:27.360 --> 1:00:28.680
- is all super important.
-
-1:00:28.680 --> 1:00:32.880
- And it's this amazing trifecta that only Google can do.
-
-1:00:32.880 --> 1:00:34.240
- Yeah, that's super exciting.
-
-1:00:34.240 --> 1:00:39.800
- So can you tell me about MLIR project, previously
-
-1:00:39.800 --> 1:00:41.400
- the secretive one?
-
-1:00:41.400 --> 1:00:43.040
- Yeah, so MLIR is a project that we
-
-1:00:43.040 --> 1:00:47.000
- announced at a compiler conference three weeks ago
-
-1:00:47.000 --> 1:00:49.280
- or something at the Compilers for Machine Learning
-
-1:00:49.280 --> 1:00:50.920
- conference.
-
-1:00:50.920 --> 1:00:53.760
- Basically, again, if you look at TensorFlow as a compiler stack,
-
-1:00:53.760 --> 1:00:56.120
- it has a number of compiler algorithms within it.
-
-1:00:56.120 --> 1:00:57.660
- It also has a number of compilers
-
-1:00:57.660 --> 1:00:59.000
- that get embedded into it.
-
-1:00:59.000 --> 1:01:00.480
- And they're made by different vendors.
-
-1:01:00.480 --> 1:01:02.840
- For example, Google has XLA, which
-
-1:01:02.840 --> 1:01:04.680
- is a great compiler system.
-
-1:01:04.680 --> 1:01:06.480
- NVIDIA has TensorRT.
-
-1:01:06.480 --> 1:01:08.640
- Intel has NGRAPH.
-
-1:01:08.640 --> 1:01:10.840
- There's a number of these different compiler systems.
-
-1:01:10.840 --> 1:01:13.840
- And they're very hardware specific.
-
-1:01:13.840 --> 1:01:16.480
- And they're trying to solve different parts of the problems.
-
-1:01:16.480 --> 1:01:19.400
- But they're all kind of similar in a sense of they
-
-1:01:19.400 --> 1:01:20.880
- want to integrate with TensorFlow.
-
-1:01:20.880 --> 1:01:22.960
- Now, TensorFlow has an optimizer.
-
-1:01:22.960 --> 1:01:25.540
- And it has these different code generation technologies
-
-1:01:25.540 --> 1:01:26.440
- built in.
-
-1:01:26.440 --> 1:01:28.720
- The idea of MLIR is to build a common infrastructure
-
-1:01:28.720 --> 1:01:31.160
- to support all these different subsystems.
-
-1:01:31.160 --> 1:01:33.500
- And initially, it's to be able to make it
-
-1:01:33.500 --> 1:01:34.880
- so that they all plug in together
-
-1:01:34.880 --> 1:01:37.880
- and they can share a lot more code and can be reusable.
-
-1:01:37.880 --> 1:01:39.680
- But over time, we hope that the industry
-
-1:01:39.680 --> 1:01:42.480
- will start collaborating and sharing code.
-
-1:01:42.480 --> 1:01:45.320
- And instead of reinventing the same things over and over again,
-
-1:01:45.320 --> 1:01:49.280
- that we can actually foster some of that working together
-
-1:01:49.280 --> 1:01:51.560
- to solve common problem energy that
-
-1:01:51.560 --> 1:01:54.480
- has been useful in the compiler field before.
-
-1:01:54.480 --> 1:01:57.360
- Beyond that, MLIR is some people have joked
-
-1:01:57.360 --> 1:01:59.320
- that it's kind of LLVM too.
-
-1:01:59.320 --> 1:02:01.840
- It learns a lot about what LLVM has been good
-
-1:02:01.840 --> 1:02:04.360
- and what LLVM has done wrong.
-
-1:02:04.360 --> 1:02:06.880
- And it's a chance to fix that.
-
-1:02:06.880 --> 1:02:09.840
- And also, there are challenges in the LLVM ecosystem as well,
-
-1:02:09.840 --> 1:02:12.760
- where LLVM is very good at the thing it was designed to do.
-
-1:02:12.760 --> 1:02:15.560
- But 20 years later, the world has changed.
-
-1:02:15.560 --> 1:02:17.980
- And people are trying to solve higher level problems.
-
-1:02:17.980 --> 1:02:20.360
- And we need some new technology.
-
-1:02:20.360 --> 1:02:24.720
- And what's the future of open source in this context?
-
-1:02:24.720 --> 1:02:25.760
- Very soon.
-
-1:02:25.760 --> 1:02:27.480
- So it is not yet open source.
-
-1:02:27.480 --> 1:02:29.320
- But it will be hopefully in the next couple months.
-
-1:02:29.320 --> 1:02:31.040
- So you still believe in the value of open source
-
-1:02:31.040 --> 1:02:31.640
- in these kinds of contexts?
-
-1:02:31.640 --> 1:02:31.880
- Oh, yeah.
-
-1:02:31.880 --> 1:02:32.440
- Absolutely.
-
-1:02:32.440 --> 1:02:36.160
- And I think that the TensorFlow community at large
-
-1:02:36.160 --> 1:02:37.720
- fully believes in open source.
-
-1:02:37.720 --> 1:02:40.120
- So I mean, there is a difference between Apple,
-
-1:02:40.120 --> 1:02:42.480
- where you were previously, and Google now,
-
-1:02:42.480 --> 1:02:43.520
- in spirit and culture.
-
-1:02:43.520 --> 1:02:45.480
- And I would say the open source in TensorFlow
-
-1:02:45.480 --> 1:02:48.400
- was a seminal moment in the history of software,
-
-1:02:48.400 --> 1:02:51.680
- because here's this large company releasing
-
-1:02:51.680 --> 1:02:56.200
- a very large code base that's open sourcing.
-
-1:02:56.200 --> 1:02:58.520
- What are your thoughts on that?
-
-1:02:58.520 --> 1:03:00.840
- Happy or not, were you to see that kind
-
-1:03:00.840 --> 1:03:02.920
- of degree of open sourcing?
-
-1:03:02.920 --> 1:03:05.360
- So between the two, I prefer the Google approach,
-
-1:03:05.360 --> 1:03:07.800
- if that's what you're saying.
-
-1:03:07.800 --> 1:03:12.400
- The Apple approach makes sense, given the historical context
-
-1:03:12.400 --> 1:03:13.400
- that Apple came from.
-
-1:03:13.400 --> 1:03:15.760
- But that's been 35 years ago.
-
-1:03:15.760 --> 1:03:18.200
- And I think that Apple is definitely adapting.
-
-1:03:18.200 --> 1:03:20.280
- And the way I look at it is that there's
-
-1:03:20.280 --> 1:03:23.160
- different kinds of concerns in the space.
-
-1:03:23.160 --> 1:03:24.880
- It is very rational for a business
-
-1:03:24.880 --> 1:03:28.720
- to care about making money.
-
-1:03:28.720 --> 1:03:31.640
- That fundamentally is what a business is about.
-
-1:03:31.640 --> 1:03:34.880
- But I think it's also incredibly realistic to say,
-
-1:03:34.880 --> 1:03:36.360
- it's not your string library that's
-
-1:03:36.360 --> 1:03:38.080
- the thing that's going to make you money.
-
-1:03:38.080 --> 1:03:41.480
- It's going to be the amazing UI product differentiating
-
-1:03:41.480 --> 1:03:43.840
- features and other things like that that you built on top
-
-1:03:43.840 --> 1:03:45.280
- of your string library.
-
-1:03:45.280 --> 1:03:48.280
- And so keeping your string library
-
-1:03:48.280 --> 1:03:50.360
- proprietary and secret and things
-
-1:03:50.360 --> 1:03:54.760
- like that is maybe not the important thing anymore.
-
-1:03:54.760 --> 1:03:57.720
- Where before, platforms were different.
-
-1:03:57.720 --> 1:04:01.520
- And even 15 years ago, things were a little bit different.
-
-1:04:01.520 --> 1:04:02.920
- But the world is changing.
-
-1:04:02.920 --> 1:04:04.840
- So Google strikes a very good balance,
-
-1:04:04.840 --> 1:04:05.340
- I think.
-
-1:04:05.340 --> 1:04:09.040
- And I think that TensorFlow being open source really
-
-1:04:09.040 --> 1:04:12.000
- changed the entire machine learning field
-
-1:04:12.000 --> 1:04:14.080
- and caused a revolution in its own right.
-
-1:04:14.080 --> 1:04:17.560
- And so I think it's amazingly forward looking
-
-1:04:17.560 --> 1:04:20.880
- because I could have imagined, and I wasn't at Google
-
-1:04:20.880 --> 1:04:23.160
- at the time, but I could imagine a different context
-
-1:04:23.160 --> 1:04:25.520
- and different world where a company says,
-
-1:04:25.520 --> 1:04:27.640
- machine learning is critical to what we're doing.
-
-1:04:27.640 --> 1:04:29.640
- We're not going to give it to other people.
-
-1:04:29.640 --> 1:04:35.560
- And so that decision is a profoundly brilliant insight
-
-1:04:35.560 --> 1:04:37.480
- that I think has really led to the world being
-
-1:04:37.480 --> 1:04:40.120
- better and better for Google as well.
-
-1:04:40.120 --> 1:04:42.200
- And has all kinds of ripple effects.
-
-1:04:42.200 --> 1:04:45.160
- I think it is really, I mean, you
-
-1:04:45.160 --> 1:04:48.800
- can't understate Google deciding how profound that
-
-1:04:48.800 --> 1:04:49.840
- is for software.
-
-1:04:49.840 --> 1:04:50.880
- It's awesome.
-
-1:04:50.880 --> 1:04:54.900
- Well, and again, I can understand the concern
-
-1:04:54.900 --> 1:04:58.440
- about if we release our machine learning software,
-
-1:04:58.440 --> 1:05:00.000
- our competitors could go faster.
-
-1:05:00.000 --> 1:05:02.500
- But on the other hand, I think that open sourcing TensorFlow
-
-1:05:02.500 --> 1:05:03.960
- has been fantastic for Google.
-
-1:05:03.960 --> 1:05:09.120
- And I'm sure that decision was very nonobvious at the time,
-
-1:05:09.120 --> 1:05:11.480
- but I think it's worked out very well.
-
-1:05:11.480 --> 1:05:13.240
- So let's try this real quick.
-
-1:05:13.240 --> 1:05:15.640
- You were at Tesla for five months
-
-1:05:15.640 --> 1:05:17.640
- as the VP of autopilot software.
-
-1:05:17.640 --> 1:05:20.520
- You led the team during the transition from H hardware
-
-1:05:20.520 --> 1:05:22.360
- one to hardware two.
-
-1:05:22.360 --> 1:05:23.520
- I have a couple of questions.
-
-1:05:23.520 --> 1:05:26.320
- So one, first of all, to me, that's
-
-1:05:26.320 --> 1:05:33.000
- one of the bravest engineering decisions undertaking really
-
-1:05:33.000 --> 1:05:36.040
- ever in the automotive industry to me, software wise,
-
-1:05:36.040 --> 1:05:37.440
- starting from scratch.
-
-1:05:37.440 --> 1:05:39.200
- It's a really brave engineering decision.
-
-1:05:39.200 --> 1:05:42.600
- So my one question there is, what was that like?
-
-1:05:42.600 --> 1:05:43.920
- What was the challenge of that?
-
-1:05:43.920 --> 1:05:45.720
- Do you mean the career decision of jumping
-
-1:05:45.720 --> 1:05:48.800
- from a comfortable good job into the unknown, or?
-
-1:05:48.800 --> 1:05:51.480
- That combined, so at the individual level,
-
-1:05:51.480 --> 1:05:54.560
- you making that decision.
-
-1:05:54.560 --> 1:05:57.960
- And then when you show up, it's a really hard engineering
-
-1:05:57.960 --> 1:05:58.760
- problem.
-
-1:05:58.760 --> 1:06:03.560
- So you could just stay, maybe slow down,
-
-1:06:03.560 --> 1:06:06.680
- say hardware one, or those kinds of decisions.
-
-1:06:06.680 --> 1:06:10.160
- Just taking it full on, let's do this from scratch.
-
-1:06:10.160 --> 1:06:11.080
- What was that like?
-
-1:06:11.080 --> 1:06:12.640
- Well, so I mean, I don't think Tesla
-
-1:06:12.640 --> 1:06:16.080
- has a culture of taking things slow and seeing how it goes.
-
-1:06:16.080 --> 1:06:18.080
- And one of the things that attracted me about Tesla
-
-1:06:18.080 --> 1:06:20.020
- is it's very much a gung ho, let's change the world,
-
-1:06:20.020 --> 1:06:21.520
- let's figure it out kind of a place.
-
-1:06:21.520 --> 1:06:25.640
- And so I have a huge amount of respect for that.
-
-1:06:25.640 --> 1:06:28.680
- Tesla has done very smart things with hardware one
-
-1:06:28.680 --> 1:06:29.400
- in particular.
-
-1:06:29.400 --> 1:06:32.200
- And the hardware one design was originally
-
-1:06:32.200 --> 1:06:36.560
- designed to be very simple automation features
-
-1:06:36.560 --> 1:06:39.360
- in the car for like traffic aware cruise control and things
-
-1:06:39.360 --> 1:06:39.840
- like that.
-
-1:06:39.840 --> 1:06:42.920
- And the fact that they were able to effectively feature creep
-
-1:06:42.920 --> 1:06:47.720
- it into lane holding and a very useful driver assistance
-
-1:06:47.720 --> 1:06:50.120
- feature is pretty astounding, particularly given
-
-1:06:50.120 --> 1:06:52.560
- the details of the hardware.
-
-1:06:52.560 --> 1:06:54.640
- Hardware two built on that in a lot of ways.
-
-1:06:54.640 --> 1:06:56.180
- And the challenge there was that they
-
-1:06:56.180 --> 1:07:00.040
- were transitioning from a third party provided vision stack
-
-1:07:00.040 --> 1:07:01.720
- to an in house built vision stack.
-
-1:07:01.720 --> 1:07:05.680
- And so for the first step, which I mostly helped with,
-
-1:07:05.680 --> 1:07:08.480
- was getting onto that new vision stack.
-
-1:07:08.480 --> 1:07:10.800
- And that was very challenging.
-
-1:07:10.800 --> 1:07:14.000
- And it was time critical for various reasons,
-
-1:07:14.000 --> 1:07:14.960
- and it was a big leap.
-
-1:07:14.960 --> 1:07:16.640
- But it was fortunate that it built
-
-1:07:16.640 --> 1:07:18.800
- on a lot of the knowledge and expertise and the team
-
-1:07:18.800 --> 1:07:22.920
- that had built hardware one's driver assistance features.
-
-1:07:22.920 --> 1:07:25.360
- So you spoke in a collected and kind way
-
-1:07:25.360 --> 1:07:28.960
- about your time at Tesla, but it was ultimately not a good fit.
-
-1:07:28.960 --> 1:07:31.840
- Elon Musk, we've talked on this podcast,
-
-1:07:31.840 --> 1:07:33.880
- several guests to the course, Elon Musk
-
-1:07:33.880 --> 1:07:36.880
- continues to do some of the most bold and innovative engineering
-
-1:07:36.880 --> 1:07:39.560
- work in the world, at times at the cost
-
-1:07:39.560 --> 1:07:41.280
- some of the members of the Tesla team.
-
-1:07:41.280 --> 1:07:45.080
- What did you learn about working in this chaotic world
-
-1:07:45.080 --> 1:07:46.720
- with Elon?
-
-1:07:46.720 --> 1:07:50.560
- Yeah, so I guess I would say that when I was at Tesla,
-
-1:07:50.560 --> 1:07:54.440
- I experienced and saw the highest degree of turnover
-
-1:07:54.440 --> 1:07:58.240
- I'd ever seen in a company, which was a bit of a shock.
-
-1:07:58.240 --> 1:08:00.520
- But one of the things I learned and I came to respect
-
-1:08:00.520 --> 1:08:03.760
- is that Elon's able to attract amazing talent because he
-
-1:08:03.760 --> 1:08:05.660
- has a very clear vision of the future,
-
-1:08:05.660 --> 1:08:07.200
- and he can get people to buy into it
-
-1:08:07.200 --> 1:08:09.840
- because they want that future to happen.
-
-1:08:09.840 --> 1:08:11.840
- And the power of vision is something
-
-1:08:11.840 --> 1:08:14.240
- that I have a tremendous amount of respect for.
-
-1:08:14.240 --> 1:08:17.040
- And I think that Elon is fairly singular
-
-1:08:17.040 --> 1:08:20.120
- in the world in terms of the things
-
-1:08:20.120 --> 1:08:22.360
- he's able to get people to believe in.
-
-1:08:22.360 --> 1:08:27.360
- And there are many people that stand in the street corner
-
-1:08:27.360 --> 1:08:30.200
- and say, ah, we're going to go to Mars, right?
-
-1:08:30.200 --> 1:08:31.600
- But then there are a few people that
-
-1:08:31.600 --> 1:08:35.200
- can get others to buy into it and believe and build the path
-
-1:08:35.200 --> 1:08:36.160
- and make it happen.
-
-1:08:36.160 --> 1:08:39.120
- And so I respect that.
-
-1:08:39.120 --> 1:08:41.880
- I don't respect all of his methods,
-
-1:08:41.880 --> 1:08:45.000
- but I have a huge amount of respect for that.
-
-1:08:45.000 --> 1:08:46.920
- You've mentioned in a few places,
-
-1:08:46.920 --> 1:08:50.440
- including in this context, working hard.
-
-1:08:50.440 --> 1:08:52.000
- What does it mean to work hard?
-
-1:08:52.000 --> 1:08:53.520
- And when you look back at your life,
-
-1:08:53.520 --> 1:08:57.080
- what were some of the most brutal periods
-
-1:08:57.080 --> 1:09:00.760
- of having to really put everything
-
-1:09:00.760 --> 1:09:03.360
- you have into something?
-
-1:09:03.360 --> 1:09:05.040
- Yeah, good question.
-
-1:09:05.040 --> 1:09:07.440
- So working hard can be defined a lot of different ways,
-
-1:09:07.440 --> 1:09:12.480
- so a lot of hours, and so that is true.
-
-1:09:12.480 --> 1:09:14.520
- The thing to me that's the hardest
-
-1:09:14.520 --> 1:09:18.760
- is both being short term focused on delivering and executing
-
-1:09:18.760 --> 1:09:21.120
- and making a thing happen while also thinking
-
-1:09:21.120 --> 1:09:24.400
- about the longer term and trying to balance that.
-
-1:09:24.400 --> 1:09:28.520
- Because if you are myopically focused on solving a task
-
-1:09:28.520 --> 1:09:31.240
- and getting that done and only think
-
-1:09:31.240 --> 1:09:32.600
- about that incremental next step,
-
-1:09:32.600 --> 1:09:36.440
- you will miss the next big hill you should jump over to.
-
-1:09:36.440 --> 1:09:39.600
- And so I've been really fortunate that I've
-
-1:09:39.600 --> 1:09:42.120
- been able to kind of oscillate between the two.
-
-1:09:42.120 --> 1:09:45.480
- And historically at Apple, for example, that
-
-1:09:45.480 --> 1:09:47.920
- was made possible because I was able to work with some really
-
-1:09:47.920 --> 1:09:50.360
- amazing people and build up teams and leadership
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-1:09:50.360 --> 1:09:55.280
- structures and allow them to grow in their careers
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-1:09:55.280 --> 1:09:58.280
- and take on responsibility, thereby freeing up
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-1:09:58.280 --> 1:10:02.960
- me to be a little bit crazy and thinking about the next thing.
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-1:10:02.960 --> 1:10:04.640
- And so it's a lot of that.
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-1:10:04.640 --> 1:10:06.760
- But it's also about with experience,
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-1:10:06.760 --> 1:10:10.080
- you make connections that other people don't necessarily make.
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-1:10:10.080 --> 1:10:12.880
- And so I think that's a big part as well.
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-1:10:12.880 --> 1:10:16.000
- But the bedrock is just a lot of hours.
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-1:10:16.000 --> 1:10:19.600
- And that's OK with me.
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-1:10:19.600 --> 1:10:21.480
- There's different theories on work life balance.
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-1:10:21.480 --> 1:10:25.200
- And my theory for myself, which I do not project onto the team,
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-1:10:25.200 --> 1:10:28.520
- but my theory for myself is that I
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- want to love what I'm doing and work really hard.
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-1:10:30.400 --> 1:10:35.000
- And my purpose, I feel like, and my goal is to change the world
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-1:10:35.000 --> 1:10:36.280
- and make it a better place.
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-1:10:36.280 --> 1:10:40.000
- And that's what I'm really motivated to do.
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-1:10:40.000 --> 1:10:44.760
- So last question, LLVM logo is a dragon.
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-1:10:44.760 --> 1:10:47.880
- You explain that this is because dragons have connotations
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-1:10:47.880 --> 1:10:50.320
- of power, speed, intelligence.
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-1:10:50.320 --> 1:10:53.320
- It can also be sleek, elegant, and modular,
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-1:10:53.320 --> 1:10:56.280
- though you remove the modular part.
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-1:10:56.280 --> 1:10:58.920
- What is your favorite dragon related character
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-1:10:58.920 --> 1:11:01.440
- from fiction, video, or movies?
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-1:11:01.440 --> 1:11:03.840
- So those are all very kind ways of explaining it.
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-1:11:03.840 --> 1:11:06.200
- Do you want to know the real reason it's a dragon?
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-1:11:06.200 --> 1:11:07.000
- Yeah.
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-1:11:07.000 --> 1:11:07.920
- Is that better?
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-1:11:07.920 --> 1:11:11.040
- So there is a seminal book on compiler design
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-1:11:11.040 --> 1:11:12.520
- called The Dragon Book.
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-1:11:12.520 --> 1:11:16.320
- And so this is a really old now book on compilers.
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-1:11:16.320 --> 1:11:22.080
- And so the dragon logo for LLVM came about because at Apple,
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-1:11:22.080 --> 1:11:24.720
- we kept talking about LLVM related technologies
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-1:11:24.720 --> 1:11:26.960
- and there's no logo to put on a slide.
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-1:11:26.960 --> 1:11:28.480
- And so we're like, what do we do?
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-1:11:28.480 --> 1:11:30.480
- And somebody's like, well, what kind of logo
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-1:11:30.480 --> 1:11:32.160
- should a compiler technology have?
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-1:11:32.160 --> 1:11:33.360
- And I'm like, I don't know.
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-1:11:33.360 --> 1:11:37.320
- I mean, the dragon is the best thing that we've got.
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-1:11:37.320 --> 1:11:41.520
- And Apple somehow magically came up with the logo.
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-1:11:41.520 --> 1:11:42.680
- And it was a great thing.
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-1:11:42.680 --> 1:11:44.520
- And the whole community rallied around it.
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-1:11:44.520 --> 1:11:46.760
- And then it got better as other graphic designers
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-1:11:46.760 --> 1:11:47.360
- got involved.
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-1:11:47.360 --> 1:11:49.360
- But that's originally where it came from.
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-1:11:49.360 --> 1:11:50.160
- The story.
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-1:11:50.160 --> 1:11:51.960
- Is there dragons from fiction that you
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-1:11:51.960 --> 1:11:57.240
- connect with, that Game of Thrones, Lord of the Rings,
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-1:11:57.240 --> 1:11:58.080
- that kind of thing?
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-1:11:58.080 --> 1:11:59.200
- Lord of the Rings is great.
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-1:11:59.200 --> 1:12:00.760
- I also like role playing games and things
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-1:12:00.760 --> 1:12:02.240
- like computer role playing games.
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-1:12:02.240 --> 1:12:04.280
- And so dragons often show up in there.
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-1:12:04.280 --> 1:12:07.160
- But really, it comes back to the book.
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-1:12:07.160 --> 1:12:09.960
- Oh, no, we need a thing.
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-1:12:09.960 --> 1:12:13.720
- And hilariously, one of the funny things about LLVM
-
-1:12:13.720 --> 1:12:19.520
- is that my wife, who's amazing, runs the LLVM Foundation.
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-1:12:19.520 --> 1:12:21.080
- And she goes to Grace Hopper and is
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-1:12:21.080 --> 1:12:23.360
- trying to get more women involved in the.
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-1:12:23.360 --> 1:12:24.640
- She's also a compiler engineer.
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-1:12:24.640 --> 1:12:26.080
- So she's trying to get other women
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-1:12:26.080 --> 1:12:28.020
- to get interested in compilers and things like this.
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-1:12:28.020 --> 1:12:30.000
- And so she hands out the stickers.
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-1:12:30.000 --> 1:12:34.320
- And people like the LLVM sticker because of Game of Thrones.
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-1:12:34.320 --> 1:12:36.880
- And so sometimes culture has this helpful effect
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-1:12:36.880 --> 1:12:39.960
- to get the next generation of compiler engineers
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-1:12:39.960 --> 1:12:42.400
- engaged with the cause.
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-1:12:42.400 --> 1:12:43.320
- OK, awesome.
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-1:12:43.320 --> 1:12:44.800
- Chris, thanks so much for talking with us.
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-1:12:44.800 --> 1:13:05.920
- It's been great talking with you.
-