[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-02-23 00:41:10 +00:00
parent c9eba0bba7
commit 88ffe73184
158 changed files with 276 additions and 276 deletions

View File

@@ -324,7 +324,7 @@ for different problem sizes.</p>
0 4096.0 9.600000 9.600000
1 8192.0 19.200000 19.200000
2 16384.0 38.400001 38.400001
3 32768.0 76.800002 76.800002
3 32768.0 63.999998 63.999998
4 65536.0 127.999995 127.999995
5 131072.0 219.428568 219.428568
6 262144.0 384.000001 384.000001
@@ -339,7 +339,7 @@ for different problem sizes.</p>
15 134217728.0 849.737435 850.656574
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 44.693 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 46.577 seconds)</p>
<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>

View File

@@ -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>
<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 190.511628
0 256.0 512.000001 546.133347 188.321838
1 384.0 585.142862 585.142862 153.600004
2 512.0 655.360017 606.814814 154.566038
3 640.0 682.666684 640.000002 160.000000
4 768.0 722.823517 664.216187 162.754967
.. ... ... ... ...
93 12160.0 814.058574 405.755985 198.631953
94 12288.0 814.111783 415.661740 198.895304
95 12416.0 812.498981 412.149375 198.457532
96 12544.0 812.566838 412.971190 198.618504
97 12672.0 812.633240 412.097543 198.776477
93 12160.0 812.359066 405.333344 198.834951
94 12288.0 814.111783 415.661740 199.096718
95 12416.0 812.498981 411.296057 198.755369
96 12544.0 812.566838 412.971190 198.913776
97 12672.0 812.633240 412.097543 199.069228
[98 rows x 4 columns]
</pre></div>
@@ -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>
</ul>
</div></blockquote>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.163 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.717 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<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>

View File

@@ -569,41 +569,41 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
M cuBLAS ... Triton Triton (+ LeakyReLU)
0 256.0 2.730667 ... 2.978909 2.978909
1 384.0 7.372800 ... 8.507077 8.507077
1 384.0 7.372800 ... 7.899428 7.899428
2 512.0 14.563555 ... 16.384000 16.384000
3 640.0 22.260869 ... 24.380953 24.380953
4 768.0 32.768000 ... 34.028308 34.028308
5 896.0 39.025776 ... 39.025776 39.025776
4 768.0 32.768000 ... 35.389441 34.028308
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 51.150050 ... 53.773130 52.428801
7 1152.0 45.242181 ... 46.656000 46.656000
8 1280.0 51.200001 ... 56.888887 56.888887
9 1408.0 64.138541 ... 67.305878 67.305878
10 1536.0 79.526831 ... 79.526831 79.526831
10 1536.0 80.430545 ... 79.526831 79.526831
11 1664.0 62.929456 ... 62.492442 62.061463
12 1792.0 72.512412 ... 72.512412 71.588687
13 1920.0 69.467336 ... 70.172588 70.172588
14 2048.0 73.584279 ... 76.959706 76.608294
15 2176.0 83.500614 ... 85.632545 85.269692
16 2304.0 68.446623 ... 76.809875 76.563695
17 2432.0 71.487187 ... 84.877538 84.367759
18 2560.0 77.833728 ... 81.108913 80.709358
19 2688.0 82.823267 ... 89.888756 89.888756
20 2816.0 84.035084 ... 82.916747 82.602666
21 2944.0 82.373605 ... 82.373605 81.298583
22 3072.0 82.420822 ... 88.612060 88.473602
23 3200.0 83.660130 ... 94.955488 94.534716
24 3328.0 82.464255 ... 84.200347 84.101981
25 3456.0 79.508447 ... 86.783176 90.382926
26 3584.0 87.381330 ... 98.268190 97.628001
27 3712.0 83.386762 ... 88.326564 85.822459
28 3840.0 84.356981 ... 91.398346 84.003561
29 3968.0 90.791620 ... 83.865247 90.656713
30 4096.0 86.480498 ... 84.894196 91.491294
13 1920.0 68.776119 ... 70.172588 70.172588
14 2048.0 73.584279 ... 76.608294 76.608294
15 2176.0 83.155572 ... 85.998493 85.632545
16 2304.0 68.446623 ... 77.057651 76.563695
17 2432.0 71.305746 ... 85.134737 83.614477
18 2560.0 77.833728 ... 81.108913 80.313727
19 2688.0 83.369354 ... 89.044730 88.216412
20 2816.0 82.916747 ... 83.074685 83.074685
21 2944.0 80.640830 ... 82.509987 81.832567
22 3072.0 82.301023 ... 88.473602 88.335577
23 3200.0 83.769634 ... 95.380032 94.955488
24 3328.0 83.130825 ... 84.298943 83.613586
25 3456.0 81.271743 ... 91.304157 85.676480
26 3584.0 85.552231 ... 89.557167 94.548254
27 3712.0 85.601834 ... 86.716441 86.905039
28 3840.0 79.305843 ... 84.419358 91.587578
29 3968.0 85.932350 ... 91.062642 85.660888
30 4096.0 93.206754 ... 86.369197 85.325956
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 21.640 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 34.643 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>

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>
</dd>
</dl>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.010 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.011 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-04-low-memory-dropout-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/c9aed78977a4c05741d675a38dde3d7d/04-low-memory-dropout.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">04-low-memory-dropout.py</span></code></a></p>

View File

@@ -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
0 1024.0 311.088617 98.303995 307.200008
1 1536.0 354.461542 134.540150 341.333333
2 2048.0 423.724127 161.684218 334.367350
3 2560.0 465.454542 181.775141 330.322572
4 3072.0 511.999982 192.501302 320.556515
5 3584.0 551.384634 208.271186 311.652167
0 1024.0 311.088617 99.497980 311.088617
1 1536.0 351.085717 133.083026 344.523365
2 2048.0 427.408686 158.554837 332.108094
3 2560.0 461.954908 182.857144 328.556154
4 3072.0 519.211251 191.999993 320.556515
5 3584.0 551.384634 208.271186 309.410081
6 4096.0 568.231237 220.412561 298.796351
7 4608.0 500.416301 232.825259 287.251954
8 5120.0 527.381977 242.845844 285.104413
9 5632.0 540.671974 243.545956 290.060087
10 6144.0 544.118087 248.661056 286.879370
11 6656.0 530.710976 256.000009 285.767438
12 7168.0 505.976473 260.654538 286.242939
13 7680.0 481.253256 262.190612 278.429013
14 8192.0 462.607053 267.130429 284.939124
15 8704.0 417.791980 267.472468 284.987724
16 9216.0 430.319054 272.394084 288.751954
7 4608.0 498.162157 232.825259 287.251954
8 5120.0 529.655159 244.294240 286.433562
9 5632.0 540.671974 245.313973 291.939522
10 6144.0 548.163546 251.202731 288.000001
11 6656.0 536.053693 255.590406 286.279570
12 7168.0 516.612607 254.485198 278.820105
13 7680.0 487.619051 266.743841 284.884090
14 8192.0 467.002371 257.003920 276.912679
15 8704.0 415.300208 267.815384 286.158893
16 9216.0 430.319054 273.742580 289.887291
17 9728.0 438.857162 280.615388 289.667485
18 10240.0 447.650282 286.433562 289.811322
19 10752.0 428.651173 246.935876 290.922209
20 11264.0 429.104745 245.760001 286.676558
21 11776.0 423.089806 249.667843 288.981596
22 12288.0 420.102570 254.673582 294.323369
23 12800.0 414.574901 253.465340 289.811310
24 13312.0 412.242569 252.759501 289.916513
18 10240.0 447.650282 287.102804 290.496460
19 10752.0 433.694125 246.699797 289.616170
20 11264.0 429.104745 246.432094 286.980888
21 11776.0 422.457417 250.109737 288.981596
22 12288.0 418.909088 254.893699 294.617366
23 12800.0 414.574901 253.674644 288.721817
24 13312.0 411.711355 252.559690 289.391298
25 13824.0 406.090579 257.390218 292.056329
26 14336.0 396.387109 254.485198 286.839504
27 14848.0 386.918555 257.665934 289.481735
28 15360.0 373.495460 257.970599 287.775181
29 15872.0 370.552519 261.806182 289.899545
26 14336.0 396.387109 255.619613 289.129416
27 14848.0 386.080180 257.108233 287.844912
28 15360.0 374.634130 258.332158 288.450715
29 15872.0 367.691129 261.986243 290.341468
</pre></div>
</div>
<div class="line-block">
@@ -477,7 +477,7 @@ to download the full example code</p>
<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>
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.900 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.765 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-05-layer-norm-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/935c0dd0fbeb4b2e69588471cbb2d4b2/05-layer-norm.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">05-layer-norm.py</span></code></a></p>

View File

@@ -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>12:42.407</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:57.713</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -183,23 +183,23 @@
</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>05:21.640</p></td>
<td><p>05:34.643</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>03:23.163</p></td>
<td><p>03:23.717</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="05-layer-norm.html#sphx-glr-getting-started-tutorials-05-layer-norm-py"><span class="std std-ref">Layer Normalization</span></a> (<code class="docutils literal notranslate"><span class="pre">05-layer-norm.py</span></code>)</p></td>
<td><p>02:12.900</p></td>
<td><p>02:12.765</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>01:44.693</p></td>
<td><p>01:46.577</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>
<td><p>00:00.010</p></td>
<td><p>00:00.011</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>