[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-09-07 00:51:18 +00:00
parent c46759fc89
commit 8e1a3b0434
161 changed files with 290 additions and 290 deletions

View File

@@ -324,22 +324,22 @@ 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 341.333321
6 262144.0 384.000001 384.000001
7 524288.0 472.615390 472.615390
8 1048576.0 614.400016 614.400016
9 2097152.0 722.823517 722.823517
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 843.811163
13 33554432.0 842.004273 842.004273
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 38.916 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 40.326 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 188.321838
0 256.0 512.000001 546.133347 190.511628
1 384.0 614.400016 585.142862 153.600004
2 512.0 655.360017 606.814814 154.566038
2 512.0 655.360017 585.142849 156.038096
3 640.0 682.666684 640.000002 160.000000
4 768.0 722.823517 664.216187 162.754967
4 768.0 722.823517 664.216187 163.839992
.. ... ... ... ...
93 12160.0 812.359066 405.755985 198.936606
94 12288.0 814.111783 415.222812 199.197579
95 12416.0 812.498981 411.296057 198.954424
96 12544.0 812.566838 412.546756 199.012395
97 12672.0 812.633240 412.097543 199.264875
93 12160.0 814.058574 405.333344 199.038365
94 12288.0 814.111783 415.222812 199.298541
95 12416.0 812.498981 411.722274 198.954424
96 12544.0 812.566838 412.971190 199.111113
97 12672.0 812.633240 411.679167 199.264875
[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 22.641 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 22.377 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

@@ -576,34 +576,34 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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 80.430545 ... 79.526831 79.526831
11 1664.0 63.372618 ... 62.492442 62.061463
12 1792.0 72.983276 ... 72.512412 72.047592
13 1920.0 69.467336 ... 70.530615 70.530615
8 1280.0 51.200001 ... 56.888887 56.109587
9 1408.0 64.138541 ... 67.305878 66.485074
10 1536.0 80.430545 ... 79.526831 78.643199
11 1664.0 62.929456 ... 62.061463 62.061463
12 1792.0 72.512412 ... 72.047592 71.588687
13 1920.0 69.120002 ... 70.172588 70.530615
14 2048.0 73.908442 ... 77.314362 76.959706
15 2176.0 83.500614 ... 85.998493 85.269692
15 2176.0 83.500614 ... 86.367588 85.269692
16 2304.0 68.251065 ... 76.809875 76.563695
17 2432.0 71.305746 ... 74.918570 84.115159
18 2560.0 78.019048 ... 81.108913 80.709358
19 2688.0 83.737433 ... 89.676257 90.102270
20 2816.0 81.369790 ... 82.290955 82.916747
21 2944.0 81.967162 ... 79.865439 82.509987
22 3072.0 82.661468 ... 87.651868 86.315709
23 3200.0 79.012346 ... 89.887639 95.380032
24 3328.0 83.323259 ... 84.895397 85.602017
25 3456.0 82.604067 ... 90.281712 90.994998
26 3584.0 83.954614 ... 92.600816 97.100854
27 3712.0 85.528545 ... 89.997611 87.322855
28 3840.0 80.313725 ... 86.130841 91.172297
29 3968.0 85.810547 ... 91.403695 83.692683
30 4096.0 93.531519 ... 83.416859 86.258181
17 2432.0 71.305746 ... 74.918570 84.367759
18 2560.0 77.833728 ... 80.709358 80.908642
19 2688.0 83.186525 ... 88.836198 89.149366
20 2816.0 79.733474 ... 82.916747 82.446516
21 2944.0 82.237674 ... 82.102191 81.832567
22 3072.0 81.589488 ... 88.473602 88.473602
23 3200.0 84.656085 ... 92.485553 95.238096
24 3328.0 83.516586 ... 84.101981 84.695641
25 3456.0 81.518272 ... 89.480098 90.892410
26 3584.0 87.636833 ... 93.661869 96.424013
27 3712.0 85.528545 ... 84.766519 87.361037
28 3840.0 82.654712 ... 87.080314 91.097196
29 3968.0 86.973584 ... 91.266964 84.856701
30 4096.0 93.466385 ... 89.359338 87.267706
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 23.225 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 19.704 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

@@ -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 99.096776 307.200008
1 1536.0 354.461542 133.083026 338.201833
2 2048.0 423.724127 162.217818 325.509933
3 2560.0 461.954908 182.857144 328.556154
4 3072.0 519.211251 190.511624 317.793096
5 3584.0 551.384634 208.271186 309.410081
6 4096.0 568.231237 220.412561 302.473845
7 4608.0 498.162157 231.364016 287.251954
8 5120.0 529.655159 242.366855 284.444444
9 5632.0 540.671974 242.671458 290.060087
10 6144.0 544.118087 250.349744 286.879370
11 6656.0 534.260858 254.775119 285.257135
12 7168.0 512.000004 252.988236 277.024148
13 7680.0 481.253256 262.564106 276.341823
14 8192.0 462.607053 265.686491 281.270376
15 8704.0 416.958106 264.425310 283.056921
16 9216.0 428.651187 271.724806 289.507855
17 9728.0 438.033784 281.291575 290.027323
18 10240.0 447.650282 285.104413 288.112552
19 10752.0 430.797982 245.994291 290.594591
20 11264.0 429.786952 243.545956 283.966395
21 11776.0 424.998497 248.569911 288.391833
22 12288.0 421.302872 252.709503 293.737063
23 12800.0 415.696898 254.094291 290.909089
24 13312.0 412.242569 252.959629 291.503659
25 13824.0 403.130022 257.590056 291.799461
26 14336.0 396.844280 251.325065 284.585606
27 14848.0 381.942121 257.479779 289.012175
28 15360.0 376.547496 260.155264 289.583654
29 15872.0 366.982663 263.071829 291.452168
0 1024.0 311.088617 94.160917 292.571431
1 1536.0 351.085717 135.032961 341.333333
2 2048.0 427.408686 161.684218 323.368435
3 2560.0 465.454542 183.677138 326.808501
4 3072.0 519.211251 191.999993 317.793096
5 3584.0 554.941930 207.768111 310.527060
6 4096.0 568.231237 220.412561 299.707322
7 4608.0 500.416301 233.316456 287.999990
8 5120.0 531.948056 242.845844 288.450695
9 5632.0 542.843364 241.371422 287.591490
10 6144.0 540.131844 250.775512 288.000001
11 6656.0 532.479975 256.000009 286.279570
12 7168.0 510.480705 256.764187 281.558103
13 7680.0 483.779539 262.938666 280.547947
14 8192.0 461.521112 262.493992 276.134828
15 8704.0 416.127506 264.760452 282.673891
16 9216.0 429.483477 270.065931 286.507772
17 9728.0 438.033784 280.278512 289.308559
18 10240.0 445.217381 285.435547 289.811322
19 10752.0 430.797982 246.229020 290.594591
20 11264.0 428.424741 245.983625 286.980888
21 11776.0 423.724129 249.447482 288.981596
22 12288.0 421.302872 253.360821 294.323369
23 12800.0 414.574901 253.047766 288.993430
24 13312.0 410.652963 251.763593 290.048115
25 13824.0 403.620451 256.792581 291.799461
26 14336.0 396.844280 252.988236 285.767449
27 14848.0 380.311643 257.108233 289.246765
28 15360.0 376.932517 259.605636 288.225185
29 15872.0 368.758973 264.349752 292.122692
</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 10.519 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.098 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>12:35.312</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:33.515</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -183,19 +183,19 @@
</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>05:23.225</p></td>
<td><p>05:19.704</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>03:22.641</p></td>
<td><p>03:22.377</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>02:10.519</p></td>
<td><p>02:11.098</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>01:38.916</p></td>
<td><p>01:40.326</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>