[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-06-19 00:46:49 +00:00
parent 5de1b15fff
commit 1f4cea595d
158 changed files with 270 additions and 270 deletions

View File

@@ -323,14 +323,14 @@ for different problem sizes.</p>
size Triton Torch
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
2 16384.0 38.400001 31.999999
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
6 262144.0 341.333321 341.333321
7 524288.0 472.615390 472.615390
8 1048576.0 614.400016 614.400016
9 2097152.0 722.823517 722.823517
9 2097152.0 722.823517 702.171410
10 4194304.0 780.190482 780.190482
11 8388608.0 812.429770 812.429770
12 16777216.0 833.084721 833.084721
@@ -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 41.632 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 29.493 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 512.000001 188.321838
0 256.0 512.000001 512.000001 190.511628
1 384.0 585.142862 585.142862 153.600004
2 512.0 655.360017 606.814814 154.566038
2 512.0 655.360017 585.142849 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 406.179533 198.631953
94 12288.0 814.111783 415.661740 198.895304
95 12416.0 812.498981 412.149375 198.556711
96 12544.0 812.566838 412.971190 198.716830
97 12672.0 812.633240 412.097543 198.873965
94 12288.0 814.111783 415.661740 198.995960
95 12416.0 812.498981 411.935714 198.556711
96 12544.0 812.566838 412.971190 198.913776
97 12672.0 812.633240 412.097543 198.971549
[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 23.422 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 17.540 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

@@ -568,42 +568,42 @@ 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 2.978909 ... 3.276800 2.978909
1 384.0 7.372800 ... 8.507077 7.899428
0 256.0 2.978909 ... 2.978909 2.978909
1 384.0 7.372800 ... 7.899428 7.899428
2 512.0 14.563555 ... 15.420235 15.420235
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
6 1024.0 49.932191 ... 53.773130 52.428801
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
9 1408.0 64.138541 ... 67.305878 66.485074
10 1536.0 80.430545 ... 79.526831 78.643199
11 1664.0 63.372618 ... 62.929456 62.061463
12 1792.0 72.983276 ... 72.047592 71.135597
12 1792.0 72.983276 ... 72.512412 71.588687
13 1920.0 69.120002 ... 70.172588 70.172588
14 2048.0 73.908442 ... 76.959706 76.608294
14 2048.0 73.584279 ... 76.959706 76.608294
15 2176.0 83.155572 ... 85.998493 85.269692
16 2304.0 68.251065 ... 77.057651 76.563695
17 2432.0 71.125224 ... 85.653855 84.877538
18 2560.0 77.833728 ... 81.108913 80.908642
19 2688.0 84.108772 ... 89.888756 90.102270
20 2816.0 83.074685 ... 83.233226 83.392363
21 2944.0 81.832567 ... 83.198715 81.298583
22 3072.0 81.943708 ... 88.750943 88.473602
23 3200.0 83.224970 ... 95.808380 94.955488
24 3328.0 83.130825 ... 84.397770 84.895397
25 3456.0 80.380430 ... 88.790274 90.281712
26 3584.0 88.152348 ... 98.808123 98.483450
27 3712.0 81.482335 ... 88.326564 86.867254
28 3840.0 84.679936 ... 92.236860 88.050954
29 3968.0 93.612530 ... 84.211604 91.266964
30 4096.0 86.480498 ... 87.552332 91.772808
16 2304.0 68.056616 ... 77.057651 76.563695
17 2432.0 71.125224 ... 85.393507 84.877538
18 2560.0 77.833728 ... 81.310171 80.908642
19 2688.0 84.108772 ... 89.044736 89.254248
20 2816.0 82.602666 ... 83.712490 82.759409
21 2944.0 82.305584 ... 82.646820 82.646820
22 3072.0 81.707223 ... 88.750943 89.170242
23 3200.0 84.768213 ... 95.665176 95.096582
24 3328.0 83.034941 ... 84.695641 84.003845
25 3456.0 82.015834 ... 87.918831 89.380896
26 3584.0 87.381330 ... 98.699661 92.410473
27 3712.0 81.648830 ... 88.718781 84.946722
28 3840.0 84.874902 ... 92.236860 88.191387
29 3968.0 93.290475 ... 85.992909 91.198760
30 4096.0 89.597949 ... 85.001726 92.024493
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 44.014 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 14.729 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 0.108 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 99.497980 311.088617
0 1024.0 311.088617 99.497980 311.088617
1 1536.0 351.085717 133.083026 341.333333
2 2048.0 423.724127 162.217818 325.509933
3 2560.0 458.507457 182.857144 326.808501
4 3072.0 511.999982 191.501303 317.793096
2 2048.0 423.724127 162.217818 336.657521
3 2560.0 461.954908 182.857144 330.322572
4 3072.0 511.999982 191.501303 320.556515
5 3584.0 554.941930 208.271186 308.301075
6 4096.0 568.231237 220.412561 294.323343
7 4608.0 495.928261 231.849059 291.031570
8 5120.0 525.128191 242.845844 287.102804
9 5632.0 538.517949 243.545956 290.683877
10 6144.0 542.117638 248.661056 285.767458
11 6656.0 527.207907 256.410903 286.793541
12 7168.0 507.469040 261.844750 288.644296
13 7680.0 482.513091 260.707203 277.590365
14 8192.0 460.440290 269.326017 286.600589
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 256.410903 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 269.326017 287.018988
15 8704.0 416.958106 267.815384 284.987724
16 9216.0 428.651187 273.066667 289.507855
17 9728.0 438.857162 280.278512 288.950501
18 10240.0 447.650282 286.433562 290.153487
19 10752.0 429.364408 246.464170 290.267711
17 9728.0 439.683593 280.278512 288.950501
18 10240.0 447.650282 286.767793 290.153487
19 10752.0 428.651173 246.464170 290.267711
20 11264.0 429.104745 245.313973 285.767446
21 11776.0 421.198220 249.447482 288.686414
22 12288.0 420.102570 254.234486 294.911986
23 12800.0 415.135142 253.465340 288.180121
24 13312.0 412.242569 252.559690 290.179836
25 13824.0 404.604870 257.190689 292.571423
26 14336.0 397.761846 254.673567 286.481278
27 14848.0 383.999990 257.293872 289.012175
28 15360.0 374.443863 257.610071 286.656296
29 15872.0 366.982663 262.708969 291.229369
21 11776.0 421.198220 249.227509 288.686414
22 12288.0 420.102570 254.453844 295.059517
23 12800.0 415.135142 253.256381 288.180121
24 13312.0 412.242569 252.759501 290.179836
25 13824.0 405.098897 257.390218 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 287.775181
29 15872.0 367.336555 262.890274 291.229369
</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 12.676 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.040 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>13:01.852</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:12.814</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>05:44.014</p></td>
<td><p>05:14.729</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>03:23.422</p></td>
<td><p>03:17.540</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>02:12.676</p></td>
<td><p>02:11.040</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>01:41.632</p></td>
<td><p>01:29.493</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>00:00.108</p></td>
<td><p>00:00.011</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>