[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-08-06 00:49:10 +00:00
parent 844e79e14c
commit 73ee4b1d0d
167 changed files with 288 additions and 288 deletions

View File

@@ -322,7 +322,7 @@ for different problem sizes.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector-add-performance:
size Triton Torch
0 4096.0 9.600000 9.600000
1 8192.0 15.999999 19.200000
1 8192.0 19.200000 19.200000
2 16384.0 38.400001 38.400001
3 32768.0 76.800002 76.800002
4 65536.0 127.999995 127.999995
@@ -334,12 +334,12 @@ 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 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 46.040 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 43.896 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

@@ -374,16 +374,16 @@ 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 186.181817
1 384.0 614.400016 585.142862 153.600004
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
3 640.0 682.666684 640.000002 158.759699
4 768.0 722.823517 664.216187 162.754967
.. ... ... ... ...
93 12160.0 814.058574 406.179533 198.834951
93 12160.0 812.359066 405.755985 198.834951
94 12288.0 814.111783 415.661740 199.096718
95 12416.0 812.498981 412.149375 198.755369
96 12544.0 812.566838 412.971190 199.012395
95 12416.0 814.163950 411.296057 198.755369
96 12544.0 812.566838 412.546756 199.012395
97 12672.0 812.633240 412.097543 199.069228
[98 rows x 4 columns]
@@ -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 22.897 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 21.154 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

@@ -568,12 +568,12 @@ 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)
0 256.0 2.730667 ... 2.978909 2.978909
0 256.0 2.978909 ... 2.978909 2.978909
1 384.0 7.372800 ... 8.507077 8.507077
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 ... 40.140799 39.025776
5 896.0 39.025776 ... 39.025776 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 56.109587
@@ -581,29 +581,29 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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 ... 70.530615 70.172588
14 2048.0 73.908442 ... 77.314362 76.959706
15 2176.0 83.155572 ... 86.367588 85.269692
13 1920.0 69.120002 ... 70.530615 70.530615
14 2048.0 73.908442 ... 76.959706 76.959706
15 2176.0 83.500614 ... 86.367588 85.632545
16 2304.0 68.251065 ... 76.809875 76.563695
17 2432.0 71.305746 ... 74.918570 84.877538
18 2560.0 77.833728 ... 81.310171 81.108913
19 2688.0 83.737433 ... 89.888756 89.044730
20 2816.0 79.879498 ... 83.074685 82.446516
21 2944.0 82.921853 ... 82.646820 83.060049
22 3072.0 81.707223 ... 87.516392 88.060814
23 3200.0 80.402009 ... 93.841640 92.219022
24 3328.0 81.530349 ... 84.895397 84.397770
25 3456.0 81.932484 ... 85.043848 88.497878
26 3584.0 86.457107 ... 98.808123 93.176571
27 3712.0 81.615477 ... 86.716441 87.399253
28 3840.0 83.027026 ... 90.909991 87.355452
29 3968.0 88.873953 ... 84.097346 90.054568
30 4096.0 92.820009 ... 88.534120 90.871857
17 2432.0 71.305746 ... 85.393507 85.134737
18 2560.0 77.926278 ... 80.709358 81.108913
19 2688.0 83.186525 ... 89.044730 89.254248
20 2816.0 79.879498 ... 79.733474 83.233226
21 2944.0 82.102191 ... 83.198715 83.060049
22 3072.0 80.202695 ... 88.060814 89.310890
23 3200.0 84.432717 ... 95.451158 94.534716
24 3328.0 82.843841 ... 83.130825 84.695641
25 3456.0 82.688790 ... 90.994998 86.596744
26 3584.0 84.745889 ... 93.176571 93.467144
27 3712.0 85.309435 ... 87.783251 88.092894
28 3840.0 84.228485 ... 92.545605 86.265212
29 3968.0 93.504929 ... 86.419216 82.616073
30 4096.0 93.271527 ... 83.365047 83.938538
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 56.082 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 23.618 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 0.130 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 1024.0 307.200008 99.096776 307.200008
1 1536.0 351.085717 133.083026 338.201833
2 2048.0 423.724127 162.217818 334.367350
3 2560.0 461.954908 182.857144 330.322572
4 3072.0 515.580429 191.501303 320.556515
5 3584.0 551.384634 208.271186 308.301075
0 1024.0 307.200008 99.497980 311.088617
1 1536.0 351.085717 133.565214 344.523365
2 2048.0 423.724127 158.554837 332.108094
3 2560.0 461.954908 183.402991 332.108113
4 3072.0 511.999982 193.005236 317.793096
5 3584.0 551.384634 208.271186 311.652167
6 4096.0 568.231237 220.412561 297.890900
7 4608.0 498.162157 231.849059 287.251954
8 5120.0 525.128191 242.845844 283.787523
9 5632.0 538.517949 243.545956 291.310338
10 6144.0 544.118087 248.661056 286.322318
11 6656.0 527.207907 256.000009 286.279570
12 7168.0 505.976473 262.243907 288.160801
13 7680.0 482.513091 260.707203 277.172933
14 8192.0 460.440290 268.957600 286.600589
15 8704.0 416.958106 267.815384 285.377055
16 9216.0 428.651187 273.066667 289.507855
17 9728.0 438.857162 280.278512 288.950501
18 10240.0 447.650282 286.767793 290.153487
19 10752.0 430.079980 246.464170 290.267711
20 11264.0 429.104745 245.202718 285.767446
21 11776.0 421.198220 249.447482 288.686414
22 12288.0 420.102570 254.453844 295.207195
23 12800.0 415.135142 253.465340 288.180121
24 13312.0 412.242569 252.759501 290.179836
25 13824.0 405.098897 257.190689 292.571423
26 14336.0 397.761846 254.862216 286.481278
27 14848.0 383.999990 257.108233 289.246765
28 15360.0 374.634130 257.610071 288.000007
29 15872.0 366.982663 262.890274 291.229369
7 4608.0 500.416301 232.825259 291.031570
8 5120.0 527.381977 240.941184 285.767451
9 5632.0 540.671974 242.671458 288.820505
10 6144.0 550.208948 250.775512 287.438593
11 6656.0 537.858601 255.590406 286.793541
12 7168.0 512.000004 256.381525 280.639473
13 7680.0 485.052616 262.938666 280.975614
14 8192.0 462.607053 265.327937 278.087683
15 8704.0 417.791980 268.159180 286.945050
16 9216.0 429.483477 271.724806 289.129410
17 9728.0 438.857162 282.653752 289.667485
18 10240.0 446.025405 285.435547 288.112552
19 10752.0 432.241202 246.229020 288.967529
20 11264.0 427.746848 244.426754 284.564206
21 11776.0 421.826879 250.553197 289.277383
22 12288.0 422.510018 254.015505 294.911986
23 12800.0 415.696898 254.304635 288.450715
24 13312.0 412.242569 252.559690 291.503659
25 13824.0 405.842204 257.790206 292.313649
26 14336.0 396.844280 253.547537 286.242939
27 14848.0 382.762626 259.165092 291.375307
28 15360.0 373.117425 260.155264 289.811315
29 15872.0 365.749395 261.267482 289.019722
</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 12.430 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 10.846 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>13:17.580</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:39.525</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>05:56.082</p></td>
<td><p>05:23.618</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>03:22.897</p></td>
<td><p>03:21.154</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>02:12.430</p></td>
<td><p>02:10.846</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>01:46.040</p></td>
<td><p>01:43.896</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>00:00.130</p></td>
<td><p>00:00.011</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>