[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-09-04 00:51:14 +00:00
parent 540e088822
commit ef6b89f4f1
165 changed files with 266 additions and 266 deletions

View File

@@ -323,11 +323,11 @@ 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 31.999999 38.400001
3 32768.0 63.999998 63.999998
2 16384.0 38.400001 38.400001
3 32768.0 76.800002 76.800002
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 341.333321
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 43.492 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 45.317 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 190.511628
1 384.0 585.142862 585.142862 151.703707
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
3 640.0 682.666684 640.000002 158.759699
4 768.0 722.823517 664.216187 163.839992
4 768.0 722.823517 664.216187 162.754967
.. ... ... ... ...
93 12160.0 812.359066 405.755985 198.936606
94 12288.0 814.111783 415.222812 199.197579
95 12416.0 812.498981 411.722274 198.854847
96 12544.0 812.566838 412.546756 198.913776
97 12672.0 812.633240 411.679167 199.069228
93 12160.0 814.058574 406.179533 198.530610
94 12288.0 814.111783 415.661740 198.895304
95 12416.0 812.498981 412.149375 198.457532
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 23.586 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 22.010 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 8.507077
2 512.0 14.563555 ... 16.384000 16.384000
0 256.0 2.730667 ... 3.276800 2.978909
1 384.0 7.372800 ... 8.507077 7.899428
2 512.0 14.563555 ... 16.384000 15.420235
3 640.0 22.260869 ... 24.380953 24.380953
4 768.0 32.768000 ... 34.028308 34.028308
5 896.0 37.971025 ... 39.025776 37.971025
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 56.109587
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 68.776119 ... 70.172588 70.530615
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 72.047592
13 1920.0 69.120002 ... 70.172588 70.530615
14 2048.0 73.908442 ... 77.314362 76.959706
15 2176.0 83.155572 ... 86.367588 84.909907
16 2304.0 68.446623 ... 76.809875 76.563695
17 2432.0 71.305746 ... 75.118889 84.877538
18 2560.0 77.833728 ... 81.108913 80.511054
19 2688.0 83.552988 ... 88.628636 89.044730
20 2816.0 82.602666 ... 82.135981 82.759409
21 2944.0 81.832567 ... 79.865439 82.852924
22 3072.0 82.540970 ... 87.651868 89.170242
23 3200.0 83.989503 ... 91.822093 92.352095
24 3328.0 79.812967 ... 83.954863 84.596116
25 3456.0 81.518272 ... 90.790053 91.407671
26 3584.0 86.540320 ... 91.656871 94.847460
27 3712.0 83.947349 ... 88.015279 87.094458
28 3840.0 80.139129 ... 85.136259 91.247522
29 3968.0 85.811488 ... 91.609561 83.633532
30 4096.0 93.596744 ... 92.372834 87.267706
15 2176.0 83.500614 ... 86.367588 85.632545
16 2304.0 68.251065 ... 76.319081 76.563695
17 2432.0 71.305746 ... 74.918570 84.877538
18 2560.0 78.019048 ... 81.310171 81.108913
19 2688.0 83.552988 ... 89.888756 89.254248
20 2816.0 79.733474 ... 83.233226 82.290955
21 2944.0 82.921853 ... 78.235527 82.715407
22 3072.0 82.062468 ... 88.473602 88.197981
23 3200.0 84.656085 ... 95.238096 95.238096
24 3328.0 82.275764 ... 84.101981 84.003845
25 3456.0 81.108217 ... 84.775569 89.380896
26 3584.0 86.125852 ... 98.808123 95.350361
27 3712.0 81.548851 ... 88.797643 84.946722
28 3840.0 85.070769 ... 92.159996 86.400002
29 3968.0 92.372393 ... 84.915752 90.994735
30 4096.0 89.597949 ... 84.280321 91.678778
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 27.587 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 22.248 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 97.912354 303.407414
1 1536.0 351.085717 134.050910 341.333333
2 2048.0 423.724127 161.154101 334.367350
3 2560.0 465.454542 180.705883 330.322572
4 3072.0 515.580429 191.999993 323.368415
5 3584.0 551.384634 208.271186 311.652167
6 4096.0 568.231237 220.412561 298.796351
7 4608.0 500.416301 232.336141 287.251954
8 5120.0 525.128191 242.366855 284.444444
9 5632.0 540.671974 243.107920 289.438969
10 6144.0 544.118087 248.661056 286.322318
11 6656.0 528.953642 256.000009 285.767438
12 7168.0 507.469040 259.867079 285.293536
13 7680.0 485.052616 263.314295 280.547947
14 8192.0 460.440290 266.406514 284.115618
15 8704.0 416.127506 267.815384 284.987724
16 9216.0 428.651187 271.391419 287.999990
17 9728.0 437.213490 280.278512 289.667485
18 10240.0 448.467168 286.433562 290.496460
19 10752.0 431.518385 246.699797 290.267711
20 11264.0 430.471331 245.313973 286.980888
21 11776.0 423.089806 249.667843 288.981596
22 12288.0 419.504980 254.673582 294.617366
23 12800.0 414.016170 253.884294 289.811310
24 13312.0 411.181478 252.759501 290.443638
25 13824.0 405.594132 257.190689 292.056329
26 14336.0 394.568805 254.862216 287.198654
27 14848.0 385.245405 257.665934 289.952797
28 15360.0 376.547496 257.970599 287.326580
29 15872.0 368.046389 261.446802 290.341468
0 1024.0 311.088617 99.096776 311.088617
1 1536.0 351.085717 133.083026 338.201833
2 2048.0 423.724127 162.217818 336.657521
3 2560.0 461.954908 182.857144 330.322572
4 3072.0 515.580429 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 5120.0 525.128191 242.845844 283.787523
9 5632.0 538.517949 243.107920 290.683877
10 6144.0 542.117638 248.661056 285.767458
11 6656.0 527.207907 256.000009 286.793541
12 7168.0 505.976473 261.844750 288.160801
13 7680.0 482.513091 260.707203 277.590365
14 8192.0 460.440290 268.957600 286.600589
15 8704.0 416.958106 267.815384 284.987724
16 9216.0 428.651187 272.729961 289.507855
17 9728.0 438.857162 280.278512 288.950501
18 10240.0 447.650282 286.767793 290.496460
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 254.453844 295.207195
23 12800.0 415.696898 253.465340 288.721817
24 13312.0 412.242569 252.759501 290.179836
25 13824.0 405.098897 257.190689 292.571423
26 14336.0 397.761846 254.673567 286.242939
27 14848.0 383.999990 257.108233 289.246765
28 15360.0 374.634130 257.790220 287.550706
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 12.490 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.305 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>12:47.166</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:40.892</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>05:27.587</p></td>
<td><p>05:22.248</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>03:23.586</p></td>
<td><p>03:22.010</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>02:12.490</p></td>
<td><p>02:11.305</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>01:43.492</p></td>
<td><p>01:45.317</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>