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Philippe Tillet
2021-10-01 00:30:50 +00:00
parent 5a0c649530
commit 44010a684c
19 changed files with 83 additions and 83 deletions
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2
getting-started/installation.html
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@@ -209,7 +209,7 @@ pip install -e .
<p>Note that, if llvm-11 is not present on your system, the setup.py script will download the official LLVM11 static libraries link against that.</p>
<p>You can then test your installation by running the unit tests:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip install -r requirements-test.txt
pytest -vs .
pytest -vs test/unit/
</pre></div>
</div>
<p>and the benchmarks</p>

2
getting-started/tutorials/01-vector-add.html
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@@ -338,7 +338,7 @@ for different problem sizes.</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-01-vector-add-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/62d97d49a32414049819dd8bb8378080/01-vector-add.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">01-vector-add.py</span></code></a></p>

22
getting-started/tutorials/02-fused-softmax.html
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@@ -373,17 +373,17 @@ We will then compare its performance against (1) <code class="code docutils lite
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>softmax-performance:
N Triton Torch (native) Torch (jit)
0 256.0 512.000001 546.133347 184.089886
1 384.0 585.142862 585.142862 153.600004
2 512.0 630.153853 585.142849 154.566038
3 640.0 682.666684 640.000002 160.000000
4 768.0 702.171410 664.216187 163.839992
0 256.0 512.000001 546.133347 188.321838
1 384.0 585.142862 585.142862 151.703707
2 512.0 630.153853 585.142849 153.121496
3 640.0 682.666684 640.000002 158.759699
4 768.0 702.171410 664.216187 161.684218
.. ... ... ... ...
93 12160.0 810.666687 405.755985 199.140227
94 12288.0 810.754644 415.661740 199.399583
95 12416.0 807.544681 411.296057 198.954424
96 12544.0 807.661970 412.971190 199.209928
97 12672.0 807.776923 412.097543 199.264875
93 12160.0 810.666687 405.755985 199.038365
94 12288.0 810.754644 415.661740 199.298541
95 12416.0 809.189387 412.149375 198.854847
96 12544.0 807.661970 412.971190 199.111113
97 12672.0 807.776923 412.307051 199.167004
[98 rows x 4 columns]
</pre></div>
@@ -396,7 +396,7 @@ We will then compare its performance against (1) <code class="code docutils lite
Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.687 seconds)</p>
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<p><a class="reference download internal" download="" href="../../_downloads/d91442ac2982c4e0cc3ab0f43534afbc/02-fused-softmax.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">02-fused-softmax.py</span></code></a></p>

48
getting-started/tutorials/03-matrix-multiplication.html
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@@ -567,7 +567,7 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
M cuBLAS ... Triton Triton (+ LeakyReLU)
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@@ -575,34 +575,34 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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12 1792.0 72.983276 ... 72.047592 72.047592
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8 1280.0 51.200001 ... 56.888887 56.109587
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14 2048.0 73.908442 ... 76.959706 76.608294
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18 2560.0 78.019048 ... 81.310171 81.310171
19 2688.0 83.737433 ... 89.254248 89.888756
20 2816.0 82.602666 ... 83.074685 83.233226
21 2944.0 82.237674 ... 82.784108 82.509987
22 3072.0 82.661468 ... 88.750943 85.920732
23 3200.0 84.993363 ... 90.780140 95.522391
24 3328.0 83.613586 ... 81.346098 83.905938
25 3456.0 81.849303 ... 91.304157 87.823058
26 3584.0 83.024371 ... 94.747514 95.451583
27 3712.0 81.682211 ... 87.937800 87.937800
28 3840.0 82.778440 ... 90.723546 88.473602
29 3968.0 91.747320 ... 84.038524 91.335278
30 4096.0 91.741443 ... 85.001726 90.200084
15 2176.0 83.500614 ... 86.367588 84.909907
16 2304.0 68.446623 ... 76.563695 76.809875
17 2432.0 71.305746 ... 74.521127 85.134737
18 2560.0 77.649287 ... 81.512437 80.709358
19 2688.0 83.552988 ... 89.254248 89.570381
20 2816.0 82.759409 ... 82.916747 83.233226
21 2944.0 82.921853 ... 82.373605 82.921853
22 3072.0 82.062468 ... 88.335577 89.170242
23 3200.0 84.768213 ... 95.380032 95.238096
24 3328.0 83.130825 ... 85.398926 85.500351
25 3456.0 80.945348 ... 82.350937 85.950501
26 3584.0 86.958797 ... 98.916823 98.160909
27 3712.0 81.482335 ... 87.629253 87.170458
28 3840.0 84.615146 ... 91.930177 84.615146
29 3968.0 92.163097 ... 80.998301 84.562670
30 4096.0 88.534120 ... 83.520676 84.360608
[31 rows x 5 columns]
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 36.208 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-03-matrix-multiplication-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/d5fee5b55a64e47f1b5724ec39adf171/03-matrix-multiplication.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">03-matrix-multiplication.py</span></code></a></p>

8
getting-started/tutorials/sg_execution_times.html
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@@ -174,7 +174,7 @@
<div class="section" id="computation-times">
<span id="sphx-glr-getting-started-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline"></a></h1>
<p><strong>10:55.434</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>10:45.175</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -183,15 +183,15 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="03-matrix-multiplication.html#sphx-glr-getting-started-tutorials-03-matrix-multiplication-py"><span class="std std-ref">Matrix Multiplication</span></a> (<code class="docutils literal notranslate"><span class="pre">03-matrix-multiplication.py</span></code>)</p></td>
<td><p>05:37.929</p></td>
<td><p>05:36.208</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="02-fused-softmax.html#sphx-glr-getting-started-tutorials-02-fused-softmax-py"><span class="std std-ref">Fused Softmax</span></a> (<code class="docutils literal notranslate"><span class="pre">02-fused-softmax.py</span></code>)</p></td>
<td><p>03:27.286</p></td>
<td><p>03:23.687</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="01-vector-add.html#sphx-glr-getting-started-tutorials-01-vector-add-py"><span class="std std-ref">Vector Addition</span></a> (<code class="docutils literal notranslate"><span class="pre">01-vector-add.py</span></code>)</p></td>
<td><p>01:50.209</p></td>
<td><p>01:45.270</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="04-low-memory-dropout.html#sphx-glr-getting-started-tutorials-04-low-memory-dropout-py"><span class="std std-ref">Low-Memory Dropout</span></a> (<code class="docutils literal notranslate"><span class="pre">04-low-memory-dropout.py</span></code>)</p></td>