[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-08-02 00:50:10 +00:00
parent 54ca5217e0
commit de0c86c743
163 changed files with 283 additions and 283 deletions

View File

@@ -324,7 +324,7 @@ 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 63.999998 76.800002
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 341.333321
@@ -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 842.004273
13 33554432.0 842.004273 842.906750
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 42.417 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 43.820 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

@@ -378,13 +378,13 @@ We will then compare its performance against (1) <code class="code docutils lite
1 384.0 585.142862 585.142862 151.703707
2 512.0 655.360017 606.814814 154.566038
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 406.179533 198.936606
94 12288.0 812.429770 415.661740 199.096718
95 12416.0 814.163950 412.149375 198.854847
96 12544.0 812.566838 412.546756 199.012395
97 12672.0 812.633240 412.097543 199.069228
93 12160.0 812.359066 406.179533 198.834951
94 12288.0 814.111783 415.661740 198.995960
95 12416.0 812.498981 411.296057 198.755369
96 12544.0 812.566838 412.971190 199.012395
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 23.539 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 24.302 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
0 256.0 2.730667 ... 2.978909 2.978909
1 384.0 7.372800 ... 7.899428 7.899428
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 37.971025 ... 40.140799 39.025776
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 51.150050 ... 53.773130 52.428801
7 1152.0 45.242181 ... 47.396572 46.656000
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 ... 80.430545 79.526831
11 1664.0 62.929456 ... 62.492442 62.061463
12 1792.0 72.983276 ... 72.512412 72.047592
13 1920.0 69.120002 ... 70.530615 70.530615
14 2048.0 73.908442 ... 76.959706 76.959706
15 2176.0 83.500614 ... 85.998493 85.269692
16 2304.0 68.251065 ... 76.809875 76.563695
14 2048.0 73.908442 ... 77.314362 76.959706
15 2176.0 83.500614 ... 85.998493 85.632545
16 2304.0 68.251065 ... 76.809875 76.809875
17 2432.0 71.305746 ... 74.719317 84.877538
18 2560.0 77.833728 ... 81.310171 81.108913
19 2688.0 83.369354 ... 89.044730 88.422041
20 2816.0 78.868366 ... 83.074685 83.074685
21 2944.0 80.380696 ... 82.646820 82.921853
22 3072.0 81.943708 ... 83.146995 88.335577
23 3200.0 84.099871 ... 95.808380 94.814812
24 3328.0 83.710812 ... 84.995628 84.546440
25 3456.0 81.683457 ... 90.079964 89.183149
26 3584.0 84.229877 ... 90.367227 97.100854
27 3712.0 85.528545 ... 88.404730 87.094458
28 3840.0 82.716526 ... 86.332554 91.322872
29 3968.0 85.750244 ... 91.130650 85.751184
30 4096.0 93.466385 ... 92.309303 87.267706
18 2560.0 77.833728 ... 81.108913 80.511054
19 2688.0 83.369354 ... 89.676257 89.254248
20 2816.0 79.154642 ... 83.552120 82.916747
21 2944.0 81.967162 ... 82.646820 82.441740
22 3072.0 82.540970 ... 89.593522 86.712254
23 3200.0 80.503145 ... 91.756271 93.158662
24 3328.0 82.275764 ... 84.795401 85.602017
25 3456.0 82.688790 ... 91.046379 88.400840
26 3584.0 87.381330 ... 97.522120 98.160909
27 3712.0 84.159518 ... 88.326564 83.040189
28 3840.0 84.164384 ... 92.159996 85.333335
29 3968.0 92.723355 ... 84.038524 91.130650
30 4096.0 87.495257 ... 86.536250 91.992956
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 24.435 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 23.071 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 98.303995 307.200008
1 1536.0 354.461542 135.032961 341.333333
2 2048.0 423.724127 160.104230 323.368435
3 2560.0 461.954908 180.705883 326.808501
4 3072.0 519.211251 191.999993 319.168834
5 3584.0 551.384634 208.776702 309.410081
6 4096.0 568.231237 220.907859 300.623865
7 4608.0 500.416301 232.825259 292.571431
8 5120.0 527.381977 244.294240 289.129408
9 5632.0 545.032265 244.869560 291.310338
10 6144.0 550.208948 251.202731 288.563606
11 6656.0 539.675652 256.410903 286.793541
12 7168.0 512.000004 253.734520 277.470965
13 7680.0 491.519996 267.130429 284.884090
14 8192.0 463.698115 259.377306 280.467910
15 8704.0 416.958106 267.130429 285.377055
16 9216.0 430.319054 273.742580 289.887291
17 9728.0 438.033784 280.615388 288.950501
18 10240.0 446.836366 286.767793 289.811322
19 10752.0 431.518385 246.699797 289.941565
20 11264.0 430.471331 245.313973 285.465683
21 11776.0 421.826879 249.227509 289.277383
22 12288.0 418.909088 254.893699 294.617366
23 12800.0 414.574901 253.674644 289.811310
24 13312.0 412.242569 252.559690 290.179836
25 13824.0 404.604870 257.190689 292.313649
26 14336.0 398.683664 256.000002 289.129416
27 14848.0 382.351933 257.479779 289.012175
28 15360.0 377.704925 258.151252 288.000007
29 15872.0 368.046389 261.806182 289.899545
0 1024.0 311.088617 93.801531 292.571431
1 1536.0 351.085717 135.529409 344.523365
2 2048.0 423.724127 161.684218 325.509933
3 2560.0 461.954908 183.402991 330.322572
4 3072.0 519.211251 191.999993 317.793096
5 3584.0 551.384634 208.271186 309.410081
6 4096.0 564.965515 220.907859 301.546004
7 4608.0 500.416301 233.316456 292.571431
8 5120.0 529.655159 242.845844 287.775181
9 5632.0 536.380957 243.545956 290.683877
10 6144.0 544.118087 250.349744 286.322318
11 6656.0 534.260858 255.182111 284.748652
12 7168.0 510.480705 255.619613 278.820105
13 7680.0 486.332448 265.208635 280.975614
14 8192.0 460.440290 266.046015 282.482757
15 8704.0 417.791980 264.425310 283.826081
16 9216.0 428.651187 270.065931 286.879380
17 9728.0 438.857162 281.971008 288.593329
18 10240.0 446.025405 286.100109 289.129408
19 10752.0 429.364408 246.699797 290.267711
20 11264.0 429.104745 245.091565 286.372873
21 11776.0 423.724129 248.569911 288.097854
22 12288.0 420.701865 252.493141 294.323369
23 12800.0 415.135142 253.465340 287.640454
24 13312.0 411.711355 253.160074 290.707920
25 13824.0 406.588243 257.790206 292.571423
26 14336.0 396.844280 254.109315 287.438588
27 14848.0 386.080180 256.737757 290.662311
28 15360.0 373.874218 259.422943 289.811315
29 15872.0 370.913333 263.071829 291.452168
</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 11.851 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.781 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>12:42.252</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:42.984</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>05:24.435</p></td>
<td><p>05:23.071</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>03:23.539</p></td>
<td><p>03:24.302</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>02:11.851</p></td>
<td><p>02:11.781</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>01:42.417</p></td>
<td><p>01:43.820</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>