[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-08-12 00:47:45 +00:00
parent ca12a57c3b
commit c32c097ece
167 changed files with 278 additions and 278 deletions

View File

@@ -324,10 +324,10 @@ 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
6 262144.0 341.333321 384.000001
7 524288.0 472.615390 472.615390
8 1048576.0 614.400016 614.400016
9 2097152.0 722.823517 722.823517
@@ -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 40.240 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 41.226 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

@@ -380,11 +380,11 @@ We will then compare its performance against (1) <code class="code docutils lite
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 198.794749
93 12160.0 814.058574 406.179533 198.429370
94 12288.0 814.111783 415.661740 198.895304
95 12416.0 812.498981 412.149375 198.457532
96 12544.0 812.566838 412.546756 198.716830
97 12672.0 812.633240 412.097543 198.873965
96 12544.0 812.566838 412.971190 198.716830
97 12672.0 812.633240 412.097543 198.776477
[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 22.452 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 20.998 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 3.276800
1 384.0 7.372800 ... 7.899428 7.899428
2 512.0 14.563555 ... 16.384000 16.384000
0 256.0 2.730667 ... 2.978909 2.978909
1 384.0 7.372800 ... 8.507077 8.507077
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 ... 39.025776 39.025776
6 1024.0 51.150050 ... 53.773130 52.428801
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 51.150050 ... 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 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 ... 72.047592 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
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 ... 70.530615 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 ... 85.134737 84.877538
18 2560.0 78.019048 ... 81.310171 80.511054
19 2688.0 83.737433 ... 89.254248 89.888756
20 2816.0 81.218262 ... 83.552120 82.759409
21 2944.0 82.237674 ... 79.865439 82.921853
22 3072.0 81.825298 ... 88.542777 86.579673
23 3200.0 79.701121 ... 91.822093 92.352095
24 3328.0 80.707733 ... 84.895397 84.596116
25 3456.0 82.099354 ... 91.304157 85.585527
26 3584.0 85.633710 ... 91.610178 95.502274
27 3712.0 84.372753 ... 87.170458 86.716441
28 3840.0 84.292684 ... 91.853823 85.399230
29 3968.0 92.372393 ... 89.068569 84.915752
30 4096.0 91.553703 ... 83.468735 86.844210
17 2432.0 71.305746 ... 85.393507 84.367759
18 2560.0 77.833728 ... 80.908642 80.908642
19 2688.0 83.737433 ... 89.254248 89.464755
20 2816.0 82.759409 ... 82.916747 82.759409
21 2944.0 81.967162 ... 82.373605 82.102191
22 3072.0 80.316458 ... 84.197924 89.240511
23 3200.0 84.880639 ... 95.952022 94.674553
24 3328.0 82.748617 ... 84.895397 84.695641
25 3456.0 81.849303 ... 91.097818 90.790053
26 3584.0 84.865870 ... 87.211821 94.548254
27 3712.0 85.455380 ... 86.192706 89.473662
28 3840.0 80.197243 ... 89.839159 88.438226
29 3968.0 85.810547 ... 84.214331 87.787005
30 4096.0 92.820009 ... 93.206754 86.313653
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 24.923 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 21.530 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 0.012 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 99.497980 311.088617
1 1536.0 351.085717 133.083026 341.333333
2 2048.0 423.724127 162.217818 336.657521
3 2560.0 465.454542 182.857144 330.322572
4 3072.0 515.580429 191.501303 320.556515
5 3584.0 554.941930 208.271186 309.410081
0 1024.0 311.088617 99.096776 307.200008
1 1536.0 351.085717 133.083026 338.201833
2 2048.0 423.724127 161.684218 336.657521
3 2560.0 461.954908 182.314537 328.556154
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 297.890900
7 4608.0 498.162157 231.849059 287.251954
8 5120.0 527.381977 242.845844 283.787523
9 5632.0 538.517949 243.545956 291.310338
10 6144.0 544.118087 248.661056 286.879370
11 6656.0 527.207907 256.000009 286.279570
12 7168.0 507.469040 262.243907 288.644296
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
7 4608.0 498.162157 231.849059 286.507772
8 5120.0 525.128191 242.845844 283.787523
9 5632.0 536.380957 243.545956 291.310338
10 6144.0 542.117638 248.661056 286.322318
11 6656.0 527.207907 256.000009 286.793541
12 7168.0 505.976473 262.243907 288.644296
13 7680.0 482.513091 260.338991 276.756754
14 8192.0 460.440290 269.326017 287.018988
15 8704.0 416.958106 267.472468 284.987724
16 9216.0 428.651187 273.066667 289.507855
17 9728.0 439.683593 280.615388 288.950501
17 9728.0 438.857162 280.615388 288.950501
18 10240.0 447.650282 286.767793 290.153487
19 10752.0 430.079980 246.464170 290.267711
20 11264.0 429.786952 245.091565 285.767446
21 11776.0 421.826879 249.227509 288.686414
22 12288.0 420.102570 254.673582 295.207195
23 12800.0 415.696898 253.465340 288.180121
24 13312.0 412.242569 252.959629 290.179836
25 13824.0 405.098897 257.390218 292.829653
19 10752.0 429.364408 246.464170 290.267711
20 11264.0 429.786952 245.313973 285.767446
21 11776.0 421.198220 249.447482 288.686414
22 12288.0 420.102570 254.673582 294.911986
23 12800.0 415.135142 253.674644 289.811310
24 13312.0 412.242569 252.659556 290.179836
25 13824.0 405.098897 257.390218 292.571423
26 14336.0 398.222222 254.862216 286.481278
27 14848.0 384.414233 257.108233 289.246765
28 15360.0 374.634130 257.790220 287.775181
29 15872.0 366.982663 262.890274 291.229369
27 14848.0 383.999990 257.293872 289.246765
28 15360.0 374.634130 257.610071 288.000007
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 9.732 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.291 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>12:37.359</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:36.056</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>05:24.923</p></td>
<td><p>05:21.530</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>03:22.452</p></td>
<td><p>03:20.998</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>02:09.732</p></td>
<td><p>02:12.291</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>01:40.240</p></td>
<td><p>01:41.226</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>00:00.012</p></td>
<td><p>00:00.011</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>