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Philippe Tillet
2022-08-04 00:49:04 +00:00
parent d84d42ef8d
commit b254e2b165
167 changed files with 284 additions and 284 deletions
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6
v1.1.2/getting-started/tutorials/01-vector-add.html
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@@ -322,8 +322,8 @@ for different problem sizes.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector-add-performance:
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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">
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<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>

16
v1.1.2/getting-started/tutorials/02-fused-softmax.html
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@@ -374,17 +374,17 @@ We will then compare its performance against (1) <code class="code docutils lite
<p class="sphx-glr-script-out">Out:</p>
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N Triton Torch (native) Torch (jit)
0 256.0 512.000001 546.133347 186.181817
0 256.0 512.000001 546.133347 192.752942
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.. ... ... ... ...
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93 12160.0 814.058574 406.179533 199.038365
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95 12416.0 812.498981 412.577363 198.954424
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@@ -397,7 +397,7 @@ 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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40
v1.1.2/getting-started/tutorials/03-matrix-multiplication.html
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@@ -568,42 +568,42 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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21 2944.0 82.237674 ... 82.373605 81.967162
22 3072.0 81.121923 ... 88.335577 88.473602
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27 3712.0 81.548851 ... 86.044224 86.791782
28 3840.0 84.809814 ... 92.083268 86.197974
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2
v1.1.2/getting-started/tutorials/04-low-memory-dropout.html
View File

@@ -371,7 +371,7 @@ to explore the <cite>triton/language/random</cite> folder!</p>
<dd><p>Nitish Srivastava and Geoffrey Hinton and Alex Krizhevsky and Ilya Sutskever and Ruslan Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting”, JMLR 2014</p>
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58
v1.1.2/getting-started/tutorials/05-layer-norm.html
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@@ -194,36 +194,36 @@ to download the full example code</p>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>layer-norm-backward:
N Triton Torch Apex
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12 7168.0 507.469040 262.243907 288.160801
13 7680.0 482.513091 260.707203 277.590365
14 8192.0 460.440290 268.957600 286.809636
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24 13312.0 412.242569 252.559690 290.179836
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<span class="n">bench_layer_norm</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">save_path</span><span class="o">=</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="n">print_data</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.847 seconds)</p>
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12
v1.1.2/getting-started/tutorials/sg_execution_times.html
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@@ -174,7 +174,7 @@
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