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<section id="cutlass-python-interface">
<h1>CUTLASS Python Interface<a class="headerlink" href="#cutlass-python-interface" title="Permalink to this heading">#</a></h1>
<p>The CUTLASS Python interface enables one to compile and run CUTLASS operations from within Python.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">cutlass</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="n">plan</span> <span class="o">=</span> <span class="n">cutlass</span><span class="o">.</span><span class="n">op</span><span class="o">.</span><span class="n">Gemm</span><span class="p">(</span><span class="n">element</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float16</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="n">cutlass</span><span class="o">.</span><span class="n">LayoutType</span><span class="o">.</span><span class="n">RowMajor</span><span class="p">)</span>
<span class="n">A</span><span class="p">,</span> <span class="n">B</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">D</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">4096</span><span class="p">,</span> <span class="mi">4096</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float16</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)]</span>
<span class="n">plan</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">B</span><span class="p">,</span> <span class="n">C</span><span class="p">,</span> <span class="n">D</span><span class="p">)</span>
</pre></div>
</div>
<p><strong>NOTE:</strong> The CUTLASS Python interface is currently an experimental release. The API may change in the future.
We welcome feedback from the community.</p>
<section id="overview">
<h2>Overview<a class="headerlink" href="#overview" title="Permalink to this heading">#</a></h2>
<p>The CUTLASS Python interface aims to provide an ease-of-use interface for using CUTLASS via Python. Toward this goal,
the CUTLASS Python interface attempts to:</p>
<ul class="simple">
<li><p>Present high-level interfaces for operators that require only few parameters</p></li>
<li><p>Select sensible default configurations for an operator given the parameters that have been specified</p></li>
<li><p>Enumerate configurations for users that are known to work in a given setting</p></li>
<li><p>Reduce the occurrence of C++ compile-time errors in favor of descriptive Python exceptions</p></li>
<li><p>Make it easy to export CUTLASS kernels to framework extensions (e.g., PyTorch CUDA extensions)</p></li>
</ul>
<section id="non-goals">
<h3>Non-goals<a class="headerlink" href="#non-goals" title="Permalink to this heading">#</a></h3>
<p>The CUTLASS Python interface does not intended to:</p>
<p><strong>Select optimal kernel configurations.</strong>
As an ease-of-use interface, the default selections for operator parameters made by the CUTLASS Python interface may
not achieve the highest possible performance in all scenarios. Users wishing to achieve the highest performance possible
should consider profile different combinations of configuration parameters, or use a library such as <a class="reference external" href="https://developer.nvidia.com/cublas">cuBLAS</a>
that contains heuristics for selecting kernels.</p>
<p><strong>Act as a fast container for CUTLASS kernels.</strong>
The CUTLASS Python interface does not strive to minimize overhead in its Python functions surrounding the running of a kernel.
Those wishing to deploy a CUTLASS kernel should consider either using the C++ emitted by the Python interface directly, or using
one of the CUTLASS emitters for automatically creating a framework extension for the kernel (e.g., a PyTorch CUDA extension).</p>
<p><strong>Act as a Python-to-CUDA-kernel JIT compilation engine.</strong>
The CUTLASS Python interface intends to enable one to use CUTLASS via Python. It can be used by frameworks for JIT compiling
Python to CUDA kernels, but does not set out to be such a framework.</p>
</section>
<section id="comparison-to-pycutlass">
<h3>Comparison to PyCUTLASS<a class="headerlink" href="#comparison-to-pycutlass" title="Permalink to this heading">#</a></h3>
<p>The CUTLASS Python interface builds atop CUTLASS’s <a class="reference external" href="https://github.com/NVIDIA/cutlass/tree/v3.0.0/tools/library/scripts/pycutlass">PyCUTLASS</a> library. PyCUTLASS enables
one to declare, compile, and run GEMMs, convolutions, and grouped GEMM operators with nearly the same configuration
space as CUTLASS’s C++ interface. While this flexibility enables one to achieve the similar levels of functionality
as available in CUTLASS’s C++ interface, it comes with the burden of needing to specify many configuration parameters
to operators – similar to what one must do in specifying template parameters to operations in CUTLASS’s C++ interface.</p>
<p>In contrast, the CUTLASS Python interface aims to provide a higher-level API for declaring, emitting, and compiling
kernels that does not require exhaustively defining template parameters.</p>
<section id="transitioning-from-pycutlass">
<h4>Transitioning from PyCUTLASS<a class="headerlink" href="#transitioning-from-pycutlass" title="Permalink to this heading">#</a></h4>
<p>At present, existing PyCUTLASS functionality remains available via the CUTLASS Python interface. One can
continue to use PyCUTLASS by replacing references to the PyCUTLASS <code class="docutils literal notranslate"><span class="pre">cutlass</span></code> module with <code class="docutils literal notranslate"><span class="pre">cutlass_bindings</span></code>
and the PyCUTLASS <code class="docutils literal notranslate"><span class="pre">pycutlass</span></code> module with <code class="docutils literal notranslate"><span class="pre">cutlass.backend</span></code>.</p>
<p>For example, the following code using PyCUTLASS:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">pycutlass</span>
<span class="kn">import</span> <span class="nn">cutlass</span>
<span class="n">math_inst</span> <span class="o">=</span> <span class="n">pycutlass</span><span class="o">.</span><span class="n">MathInstruction</span><span class="p">(</span>
<span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">cutlass</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">cutlass</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">cutlass</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span>
<span class="n">cutlass</span><span class="o">.</span><span class="n">OpClass</span><span class="o">.</span><span class="n">Simt</span><span class="p">,</span> <span class="n">pycutlass</span><span class="o">.</span><span class="n">MathOperation</span><span class="o">.</span><span class="n">multiply_add</span>
<span class="p">)</span>
</pre></div>
</div>
<p>can work with the Python interface via:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">cutlass.backend</span> <span class="k">as</span> <span class="nn">pycutlass</span>
<span class="kn">import</span> <span class="nn">cutlass_bindings</span>
<span class="n">math_inst</span> <span class="o">=</span> <span class="n">pycutlass</span><span class="o">.</span><span class="n">MathInstruction</span><span class="p">(</span>
<span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">cutlass_bindings</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">cutlass_bindings</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">cutlass_bindings</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span>
<span class="n">cutlass_bindings</span><span class="o">.</span><span class="n">OpClass</span><span class="o">.</span><span class="n">Simt</span><span class="p">,</span> <span class="n">pycutlass</span><span class="o">.</span><span class="n">MathOperation</span><span class="o">.</span><span class="n">multiply_add</span>
<span class="p">)</span>
</pre></div>
</div>
<p><strong>NOTE:</strong> backwards compatibility of <code class="docutils literal notranslate"><span class="pre">cutlass.backend</span></code> with <code class="docutils literal notranslate"><span class="pre">pycutlass</span></code> will not be maintained moving forward.</p>
</section>
</section>
</section>
<section id="current-functionality">
<h2>Current functionality<a class="headerlink" href="#current-functionality" title="Permalink to this heading">#</a></h2>
<p>The CUTLASS Python interface currently supports the following operations:</p>
<ul class="simple">
<li><p>GEMMs</p></li>
<li><p>GEMMs with fused elementwise epilogues (e.g., ReLU) (for pre-SM90 kernels)</p></li>
<li><p>Stream K swizzling (for pre-SM90 kernels)</p></li>
<li><p>Grouped GEMM (for pre-SM90 kernels)</p></li>
</ul>
</section>
<section id="getting-started">
<h2>Getting started<a class="headerlink" href="#getting-started" title="Permalink to this heading">#</a></h2>
<p>We recommend using the CUTLASS Python interface via one of the Docker images located in the <a href="#id1"><span class="problematic" id="id2">docker</span></a> directory.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker<span class="w"> </span>build<span class="w"> </span>-t<span class="w"> </span>cutlass-cuda12.1:latest<span class="w"> </span>-f<span class="w"> </span>docker/Dockerfile-cuda12.1-pytorch<span class="w"> </span>.
docker<span class="w"> </span>run<span class="w"> </span>--gpus<span class="w"> </span>all<span class="w"> </span>-it<span class="w"> </span>--rm<span class="w"> </span>cutlass-cuda12.1:latest
</pre></div>
</div>
<p>The CUTLASS Python interface has been tested with CUDA 11.8, 12.0, and 12.1 on Python 3.8.10 and 3.9.7.</p>
<section id="optional-environment-variables">
<h3>Optional environment variables<a class="headerlink" href="#optional-environment-variables" title="Permalink to this heading">#</a></h3>
<p>Prior to installing the CUTLASS Python interface, one may optionally set the following environment variables:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">CUTLASS_PATH</span></code>: the path to the cloned CUTLASS repository</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">CUDA_INSTALL_PATH</span></code>: the path to the installation of CUDA</p></li>
</ul>
<p>If these environment variables are not set, the installation process will infer them to be the following:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">CUTLASS_PATH</span></code>: one directory level above the current directory (i.e., <code class="docutils literal notranslate"><span class="pre">$(pwd)/..</span></code>)</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">CUDA_INSTALL_PATH</span></code>: the directory holding <code class="docutils literal notranslate"><span class="pre">/bin/nvcc</span></code> for the first version of <code class="docutils literal notranslate"><span class="pre">nvcc</span></code> on <code class="docutils literal notranslate"><span class="pre">$PATH</span></code> (i.e., <code class="docutils literal notranslate"><span class="pre">which</span> <span class="pre">nvcc</span> <span class="pre">|</span> <span class="pre">awk</span> <span class="pre">-F'/bin/nvcc'</span> <span class="pre">'{print</span> <span class="pre">$1}'</span></code>)</p></li>
</ul>
<p><strong>NOTE:</strong> The version of <code class="docutils literal notranslate"><span class="pre">cuda-python</span></code> installed must match the CUDA version in <code class="docutils literal notranslate"><span class="pre">CUDA_INSTALL_PATH</span></code>.</p>
</section>
<section id="installation">
<h3>Installation<a class="headerlink" href="#installation" title="Permalink to this heading">#</a></h3>
<p>The CUTLASS Python interface can currently be installed via:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>setup.py<span class="w"> </span>develop<span class="w"> </span>--user
</pre></div>
</div>
<p>This will allow changes to the Python interface source to be reflected when using the Python interface.</p>
<p>We plan to add support for installing via <code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">setup.py</span> <span class="pre">install</span></code> in a future release.</p>
</section>
</section>
<section id="examples">
<h2>Examples<a class="headerlink" href="#examples" title="Permalink to this heading">#</a></h2>
<p>Jupyter notebook examples of using the CUTLASS Python interface are located in <a href="#id3"><span class="problematic" id="id4">examples/python</span></a>.</p>
<p>To launch these notebooks from this directory, run:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>jupyter-lab<span class="w"> </span>../examples/python
</pre></div>
</div>
</section>
<section id="building-documentation">
<h2>Building documentation<a class="headerlink" href="#building-documentation" title="Permalink to this heading">#</a></h2>
<p>The CUTLASS Python interface uses <a class="reference external" href="https://www.sphinx-doc.org/en/master/">Sphinx</a> for documentation.</p>
<p>Building the documentation requires additional packages. These can be installed via:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>sudo<span class="w"> </span>apt-get<span class="w"> </span>install<span class="w"> </span>pandoc
pip<span class="w"> </span>install<span class="w"> </span>--upgrade<span class="w"> </span>Sphinx<span class="w"> </span>furo<span class="w"> </span>pandoc<span class="w"> </span>myst-parser<span class="w"> </span>sphinx-copybutton<span class="w"> </span>nbsphinx<span class="w"> </span>nbsphinx-link<span class="w"> </span>sphinx-inline-tabs
</pre></div>
</div>
<p>To build documentation, you must first have installed the CUTLASS Python interface via the
<a class="reference internal" href="install.html#installation"><span class="std std-ref">installation instructions</span></a>.</p>
<p>Documentation can then be built via the following commands:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>sphinx-apidoc<span class="w"> </span>-o<span class="w"> </span>docs_src/source/<span class="w"> </span>cutlass/<span class="w"> </span>cutlass/backend*
<span class="nb">cd</span><span class="w"> </span>docs_src
make<span class="w"> </span>html
mv<span class="w"> </span>_build/*<span class="w"> </span>../docs
</pre></div>
</div>
</section>
</section>
<section id="copyright">
<h1>Copyright<a class="headerlink" href="#copyright" title="Permalink to this heading">#</a></h1>
<p>Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: BSD-3-Clause</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">Redistribution</span> <span class="ow">and</span> <span class="n">use</span> <span class="ow">in</span> <span class="n">source</span> <span class="ow">and</span> <span class="n">binary</span> <span class="n">forms</span><span class="p">,</span> <span class="k">with</span> <span class="ow">or</span> <span class="n">without</span>
<span class="n">modification</span><span class="p">,</span> <span class="n">are</span> <span class="n">permitted</span> <span class="n">provided</span> <span class="n">that</span> <span class="n">the</span> <span class="n">following</span> <span class="n">conditions</span> <span class="n">are</span> <span class="n">met</span><span class="p">:</span>
<span class="mf">1.</span> <span class="n">Redistributions</span> <span class="n">of</span> <span class="n">source</span> <span class="n">code</span> <span class="n">must</span> <span class="n">retain</span> <span class="n">the</span> <span class="n">above</span> <span class="n">copyright</span> <span class="n">notice</span><span class="p">,</span> <span class="n">this</span>
<span class="nb">list</span> <span class="n">of</span> <span class="n">conditions</span> <span class="ow">and</span> <span class="n">the</span> <span class="n">following</span> <span class="n">disclaimer</span><span class="o">.</span>
<span class="mf">2.</span> <span class="n">Redistributions</span> <span class="ow">in</span> <span class="n">binary</span> <span class="n">form</span> <span class="n">must</span> <span class="n">reproduce</span> <span class="n">the</span> <span class="n">above</span> <span class="n">copyright</span> <span class="n">notice</span><span class="p">,</span>
<span class="n">this</span> <span class="nb">list</span> <span class="n">of</span> <span class="n">conditions</span> <span class="ow">and</span> <span class="n">the</span> <span class="n">following</span> <span class="n">disclaimer</span> <span class="ow">in</span> <span class="n">the</span> <span class="n">documentation</span>
<span class="ow">and</span><span class="o">/</span><span class="ow">or</span> <span class="n">other</span> <span class="n">materials</span> <span class="n">provided</span> <span class="k">with</span> <span class="n">the</span> <span class="n">distribution</span><span class="o">.</span>
<span class="mf">3.</span> <span class="n">Neither</span> <span class="n">the</span> <span class="n">name</span> <span class="n">of</span> <span class="n">the</span> <span class="n">copyright</span> <span class="n">holder</span> <span class="n">nor</span> <span class="n">the</span> <span class="n">names</span> <span class="n">of</span> <span class="n">its</span>
<span class="n">contributors</span> <span class="n">may</span> <span class="n">be</span> <span class="n">used</span> <span class="n">to</span> <span class="n">endorse</span> <span class="ow">or</span> <span class="n">promote</span> <span class="n">products</span> <span class="n">derived</span> <span class="kn">from</span>
<span class="nn">this</span> <span class="n">software</span> <span class="n">without</span> <span class="n">specific</span> <span class="n">prior</span> <span class="n">written</span> <span class="n">permission</span><span class="o">.</span>
<span class="n">THIS</span> <span class="n">SOFTWARE</span> <span class="n">IS</span> <span class="n">PROVIDED</span> <span class="n">BY</span> <span class="n">THE</span> <span class="n">COPYRIGHT</span> <span class="n">HOLDERS</span> <span class="n">AND</span> <span class="n">CONTRIBUTORS</span> <span class="s2">"AS IS"</span>
<span class="n">AND</span> <span class="n">ANY</span> <span class="n">EXPRESS</span> <span class="n">OR</span> <span class="n">IMPLIED</span> <span class="n">WARRANTIES</span><span class="p">,</span> <span class="n">INCLUDING</span><span class="p">,</span> <span class="n">BUT</span> <span class="n">NOT</span> <span class="n">LIMITED</span> <span class="n">TO</span><span class="p">,</span> <span class="n">THE</span>
<span class="n">IMPLIED</span> <span class="n">WARRANTIES</span> <span class="n">OF</span> <span class="n">MERCHANTABILITY</span> <span class="n">AND</span> <span class="n">FITNESS</span> <span class="n">FOR</span> <span class="n">A</span> <span class="n">PARTICULAR</span> <span class="n">PURPOSE</span> <span class="n">ARE</span>
<span class="n">DISCLAIMED</span><span class="o">.</span> <span class="n">IN</span> <span class="n">NO</span> <span class="n">EVENT</span> <span class="n">SHALL</span> <span class="n">THE</span> <span class="n">COPYRIGHT</span> <span class="n">HOLDER</span> <span class="n">OR</span> <span class="n">CONTRIBUTORS</span> <span class="n">BE</span> <span class="n">LIABLE</span>
<span class="n">FOR</span> <span class="n">ANY</span> <span class="n">DIRECT</span><span class="p">,</span> <span class="n">INDIRECT</span><span class="p">,</span> <span class="n">INCIDENTAL</span><span class="p">,</span> <span class="n">SPECIAL</span><span class="p">,</span> <span class="n">EXEMPLARY</span><span class="p">,</span> <span class="n">OR</span> <span class="n">CONSEQUENTIAL</span>
<span class="n">DAMAGES</span> <span class="p">(</span><span class="n">INCLUDING</span><span class="p">,</span> <span class="n">BUT</span> <span class="n">NOT</span> <span class="n">LIMITED</span> <span class="n">TO</span><span class="p">,</span> <span class="n">PROCUREMENT</span> <span class="n">OF</span> <span class="n">SUBSTITUTE</span> <span class="n">GOODS</span> <span class="n">OR</span>
<span class="n">SERVICES</span><span class="p">;</span> <span class="n">LOSS</span> <span class="n">OF</span> <span class="n">USE</span><span class="p">,</span> <span class="n">DATA</span><span class="p">,</span> <span class="n">OR</span> <span class="n">PROFITS</span><span class="p">;</span> <span class="n">OR</span> <span class="n">BUSINESS</span> <span class="n">INTERRUPTION</span><span class="p">)</span> <span class="n">HOWEVER</span>
<span class="n">CAUSED</span> <span class="n">AND</span> <span class="n">ON</span> <span class="n">ANY</span> <span class="n">THEORY</span> <span class="n">OF</span> <span class="n">LIABILITY</span><span class="p">,</span> <span class="n">WHETHER</span> <span class="n">IN</span> <span class="n">CONTRACT</span><span class="p">,</span> <span class="n">STRICT</span> <span class="n">LIABILITY</span><span class="p">,</span>
<span class="n">OR</span> <span class="n">TORT</span> <span class="p">(</span><span class="n">INCLUDING</span> <span class="n">NEGLIGENCE</span> <span class="n">OR</span> <span class="n">OTHERWISE</span><span class="p">)</span> <span class="n">ARISING</span> <span class="n">IN</span> <span class="n">ANY</span> <span class="n">WAY</span> <span class="n">OUT</span> <span class="n">OF</span> <span class="n">THE</span> <span class="n">USE</span>
<span class="n">OF</span> <span class="n">THIS</span> <span class="n">SOFTWARE</span><span class="p">,</span> <span class="n">EVEN</span> <span class="n">IF</span> <span class="n">ADVISED</span> <span class="n">OF</span> <span class="n">THE</span> <span class="n">POSSIBILITY</span> <span class="n">OF</span> <span class="n">SUCH</span> <span class="n">DAMAGE</span><span class="o">.</span>
</pre></div>
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<section id="indices-and-tables">
<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Permalink to this heading">#</a></h1>
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<ul>
<li><a class="reference internal" href="#">CUTLASS Python Interface</a><ul>
<li><a class="reference internal" href="#overview">Overview</a><ul>
<li><a class="reference internal" href="#non-goals">Non-goals</a></li>
<li><a class="reference internal" href="#comparison-to-pycutlass">Comparison to PyCUTLASS</a><ul>
<li><a class="reference internal" href="#transitioning-from-pycutlass">Transitioning from PyCUTLASS</a></li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#current-functionality">Current functionality</a></li>
<li><a class="reference internal" href="#getting-started">Getting started</a><ul>
<li><a class="reference internal" href="#optional-environment-variables">Optional environment variables</a></li>
<li><a class="reference internal" href="#installation">Installation</a></li>
</ul>
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<li><a class="reference internal" href="#examples">Examples</a></li>
<li><a class="reference internal" href="#building-documentation">Building documentation</a></li>
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