[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-02-13 00:39:42 +00:00
parent 2f5658c61f
commit 13537582ad
159 changed files with 303 additions and 303 deletions

View File

@@ -325,7 +325,7 @@ 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 63.999998 63.999998
3 32768.0 76.800002 76.800002
4 65536.0 127.999995 127.999995
5 131072.0 219.428568 219.428568
6 262144.0 341.333321 384.000001
@@ -335,12 +335,12 @@ for different problem sizes.</p>
10 4194304.0 780.190482 780.190482
11 8388608.0 812.429770 812.429770
12 16777216.0 833.084721 833.084721
13 33554432.0 842.004273 842.004273
13 33554432.0 842.004273 843.811163
14 67108864.0 847.448255 848.362445
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 38.414 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 42.825 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

@@ -369,17 +369,17 @@ 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)
0 256.0 546.133347 546.133347 186.181817
1 384.0 585.142862 585.142862 151.703707
2 512.0 655.360017 606.814814 156.038096
3 640.0 682.666684 640.000002 160.000000
4 768.0 722.823517 664.216187 163.839992
0 256.0 512.000001 546.133347 188.321838
1 384.0 614.400016 585.142862 153.600004
2 512.0 655.360017 606.814814 154.566038
3 640.0 706.206879 640.000002 160.000000
4 768.0 722.823517 664.216187 162.754967
.. ... ... ... ...
93 12160.0 814.058574 405.755985 198.834951
94 12288.0 814.111783 415.222812 199.096718
95 12416.0 814.163950 411.296057 198.755369
96 12544.0 814.214963 412.546756 198.864492
97 12672.0 814.265046 412.097543 199.069228
93 12160.0 815.765209 406.179533 198.631953
94 12288.0 815.800825 415.661740 198.895304
95 12416.0 814.163950 412.149375 198.457532
96 12544.0 814.214963 412.971190 198.716830
97 12672.0 814.265046 411.679167 198.679085
[98 rows x 4 columns]
</pre></div>
@@ -392,7 +392,7 @@ 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 19.681 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 22.274 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

@@ -565,41 +565,41 @@ 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 2.978909 ... 2.978909 2.978909
1 384.0 7.372800 ... 8.507077 7.899428
1 384.0 7.372800 ... 8.507077 8.192000
2 512.0 14.563555 ... 16.384000 16.384000
3 640.0 23.272727 ... 24.380953 24.380953
3 640.0 22.260869 ... 24.380953 24.380953
4 768.0 32.768000 ... 34.028308 34.028308
5 896.0 37.971025 ... 40.140799 39.025776
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 49.932191 ... 52.428801 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 66.485074
10 1536.0 80.430545 ... 79.526831 78.643199
11 1664.0 62.929456 ... 62.492442 62.492442
12 1792.0 72.512412 ... 72.047592 72.047592
13 1920.0 68.776119 ... 70.172588 70.530615
14 2048.0 73.584279 ... 76.608294 76.608294
15 2176.0 83.500614 ... 86.367588 85.998493
16 2304.0 68.643310 ... 76.809875 76.563695
17 2432.0 71.487187 ... 74.719317 84.621881
18 2560.0 77.283019 ... 81.108913 81.108913
19 2688.0 83.369354 ... 89.464755 89.676257
20 2816.0 81.981598 ... 83.392363 82.916747
21 2944.0 81.967162 ... 81.034195 81.832567
22 3072.0 82.301023 ... 87.924073 88.612060
23 3200.0 78.816219 ... 94.814812 95.380032
24 3328.0 84.101981 ... 82.275764 85.500351
25 3456.0 81.849303 ... 83.893412 90.281712
26 3584.0 87.211821 ... 98.537414 90.367227
27 3712.0 80.627396 ... 87.132441 87.018592
28 3840.0 84.940091 ... 92.236860 84.548438
29 3968.0 92.302520 ... 84.154440 90.724116
30 4096.0 86.478753 ... 90.169784 87.097813
10 1536.0 79.526831 ... 79.526831 78.643199
11 1664.0 62.929456 ... 62.492442 62.061463
12 1792.0 72.512412 ... 71.588687 72.047592
13 1920.0 69.120002 ... 70.172588 70.172588
14 2048.0 73.908442 ... 76.959706 76.260072
15 2176.0 83.155572 ... 85.998493 85.998493
16 2304.0 68.643310 ... 76.809875 76.076024
17 2432.0 71.125224 ... 84.877538 85.134737
18 2560.0 78.019048 ... 80.908642 81.108913
19 2688.0 82.642823 ... 89.995386 89.464755
20 2816.0 83.074685 ... 83.552120 82.680963
21 2944.0 81.832567 ... 81.564701 81.967162
22 3072.0 81.707223 ... 88.060814 88.612060
23 3200.0 80.706181 ... 95.167286 94.814812
24 3328.0 83.226931 ... 84.003845 84.298943
25 3456.0 79.430113 ... 84.909497 89.380896
26 3584.0 87.466332 ... 97.734120 98.160909
27 3712.0 79.917877 ... 86.942857 89.035062
28 3840.0 84.292684 ... 91.473945 86.467555
29 3968.0 90.791620 ... 80.864108 86.572497
30 4096.0 88.592559 ... 86.928580 91.366730
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 57.081 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 6 minutes 8.357 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

@@ -372,7 +372,7 @@ 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 0.497 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.489 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 1024.0 307.200008 97.912354 303.407414
0 1024.0 311.088617 98.303995 307.200008
1 1536.0 347.773587 134.540150 341.333333
2 2048.0 420.102553 161.684218 323.368435
3 2560.0 458.507457 181.238943 330.322572
2 2048.0 420.102553 161.684218 334.367350
3 2560.0 458.507457 181.775141 330.322572
4 3072.0 511.999982 192.501302 320.556515
5 3584.0 547.872604 208.271186 312.785456
6 4096.0 568.231237 220.907859 300.623865
7 4608.0 507.302750 232.825259 287.999990
8 5120.0 527.381977 242.845844 285.104413
9 5632.0 540.671974 241.371422 288.204696
10 6144.0 548.163546 250.349744 287.438593
11 6656.0 534.260858 256.000009 286.279570
12 7168.0 512.000004 255.240352 280.182402
13 7680.0 485.052616 263.690977 277.172933
14 8192.0 463.698115 268.223740 281.673345
15 8704.0 418.629245 266.109560 282.291896
16 9216.0 432.845409 272.394084 288.375482
17 9728.0 439.683593 278.606213 287.173424
18 10240.0 446.025405 286.767793 288.112552
19 10752.0 423.724151 244.827326 288.321786
20 11264.0 426.397479 245.983625 287.285864
21 11776.0 421.198220 247.807112 287.219500
22 12288.0 420.701865 254.453844 294.911986
23 12800.0 413.458944 252.009851 287.910035
24 13312.0 411.181478 253.763296 290.972683
25 13824.0 403.620451 258.191439 292.829653
26 14336.0 394.116833 255.240352 289.372589
27 14848.0 385.245405 256.552919 289.952797
28 15360.0 379.649845 262.751252 289.811315
29 15872.0 370.913333 261.806182 289.899545
5 3584.0 547.872604 208.271186 311.652167
6 4096.0 568.231237 220.412561 297.890900
7 4608.0 504.986315 232.825259 286.507772
8 5120.0 529.655159 242.845844 285.104413
9 5632.0 545.032265 243.545956 289.438969
10 6144.0 548.163546 248.661056 285.767458
11 6656.0 534.260858 256.000009 285.767438
12 7168.0 507.469040 260.457220 286.242939
13 7680.0 481.253256 262.190612 275.104486
14 8192.0 462.607053 267.130429 284.939124
15 8704.0 417.791980 267.815384 284.599455
16 9216.0 431.157889 272.394084 288.751954
17 9728.0 438.857162 280.615388 290.027323
18 10240.0 449.287041 286.433562 287.438599
19 10752.0 427.231788 247.172406 290.594591
20 11264.0 427.071098 245.760001 286.676558
21 11776.0 422.457417 249.667843 288.686414
22 12288.0 419.504980 254.453844 294.029924
23 12800.0 414.016170 253.256381 289.538159
24 13312.0 411.181478 252.759501 289.916513
25 13824.0 404.112047 257.190689 292.056329
26 14336.0 393.215988 254.485198 286.719986
27 14848.0 385.245405 257.665934 289.246765
28 15360.0 373.495460 257.970599 287.102804
29 15872.0 371.637071 261.806182 289.899545
</pre></div>
</div>
<div class="line-block">
@@ -487,7 +487,7 @@ 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 12.137 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.324 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>13:07.810</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>13:26.269</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>05:57.081</p></td>
<td><p>06:08.357</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>03:19.681</p></td>
<td><p>03:22.274</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>02:12.137</p></td>
<td><p>02:12.324</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>01:38.414</p></td>
<td><p>01:42.825</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>00:00.497</p></td>
<td><p>00:00.489</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>