[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-08-16 01:02:32 +00:00
parent 943e27aa53
commit d1343b5511
165 changed files with 306 additions and 306 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 63.999998 63.999998
4 65536.0 127.999995 127.999995
5 131072.0 219.428568 219.428568
6 262144.0 341.333321 384.000001
@@ -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 41.931 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 45.823 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
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 160.000000
4 768.0 722.823517 664.216187 162.754967
.. ... ... ... ...
93 12160.0 812.359066 406.179533 198.936606
94 12288.0 814.111783 415.661740 199.197579
95 12416.0 812.498981 412.149375 198.655991
96 12544.0 812.566838 412.546756 199.111113
97 12672.0 812.633240 412.097543 199.069228
93 12160.0 814.058574 406.179533 198.631953
94 12288.0 814.111783 416.101597 198.995960
95 12416.0 812.498981 412.149375 198.556711
96 12544.0 812.566838 412.971190 198.815254
97 12672.0 812.633240 412.097543 198.873965
[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 21.826 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.673 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 ... 2.978909 2.978909
1 384.0 7.372800 ... 8.507077 8.507077
0 256.0 2.978909 ... 3.276800 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 39.025776 ... 39.025776 39.025776
6 1024.0 51.150050 ... 52.428801 52.428801
7 1152.0 45.242181 ... 47.396572 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 ... 62.061463 62.061463
12 1792.0 72.512412 ... 72.047592 71.588687
13 1920.0 69.120002 ... 70.172588 70.172588
14 2048.0 73.908442 ... 76.959706 76.959706
15 2176.0 83.500614 ... 85.998493 85.269692
16 2304.0 68.446623 ... 76.809875 76.563695
17 2432.0 71.305746 ... 74.918570 84.877538
18 2560.0 77.833728 ... 81.310171 80.313727
19 2688.0 83.922689 ... 89.676257 88.422041
20 2816.0 80.617762 ... 83.392363 83.233226
21 2944.0 82.373605 ... 82.373605 81.298583
22 3072.0 82.540970 ... 88.335577 88.060814
23 3200.0 83.769634 ... 95.096582 94.674553
24 3328.0 84.003845 ... 83.516586 84.003845
25 3456.0 82.015834 ... 89.183149 84.597660
26 3584.0 86.043434 ... 97.416461 96.579370
27 3712.0 81.548851 ... 88.797643 84.946722
28 3840.0 83.908951 ... 91.097196 85.930069
29 3968.0 91.301109 ... 86.175099 89.068569
30 4096.0 88.534120 ... 93.206754 89.240508
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 62.929456 ... 62.061463 62.061463
12 1792.0 72.512412 ... 71.588687 71.588687
13 1920.0 68.776119 ... 70.530615 70.172588
14 2048.0 73.908442 ... 77.314362 76.959706
15 2176.0 83.500614 ... 86.367588 85.269692
16 2304.0 68.251065 ... 76.809875 76.563695
17 2432.0 71.305746 ... 74.719317 84.877538
18 2560.0 78.019048 ... 80.908642 81.108913
19 2688.0 82.913785 ... 89.254248 88.011732
20 2816.0 79.587973 ... 82.602666 81.981598
21 2944.0 81.564701 ... 81.034195 82.102191
22 3072.0 81.943708 ... 88.473602 87.112467
23 3200.0 82.901554 ... 95.522391 95.238096
24 3328.0 82.939284 ... 84.200347 84.745492
25 3456.0 82.688790 ... 83.893412 88.449333
26 3584.0 87.042978 ... 97.734120 98.160909
27 3712.0 84.159518 ... 87.208507 89.674457
28 3840.0 85.070769 ... 91.247522 84.164384
29 3968.0 91.232846 ... 84.856701 91.130650
30 4096.0 86.592080 ... 84.573239 90.871857
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 21.527 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 27.659 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 303.407414
1 1536.0 351.085717 134.540150 338.201833
2 2048.0 423.724127 161.154101 323.368435
3 2560.0 465.454542 180.705883 326.808501
4 3072.0 515.580429 191.999993 320.556515
5 3584.0 554.941930 208.271186 311.652167
6 4096.0 568.231237 220.412561 298.796351
7 4608.0 500.416301 232.825259 286.507772
8 5120.0 527.381977 241.889751 283.133649
9 5632.0 540.671974 243.107920 290.683877
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 325.509933
3 2560.0 461.954908 182.857144 326.808501
4 3072.0 511.999982 191.501303 317.793096
5 3584.0 554.941930 208.271186 308.301075
6 4096.0 568.231237 220.412561 294.323343
7 4608.0 498.162157 231.849059 291.031570
8 5120.0 525.128191 242.845844 287.102804
9 5632.0 538.517949 243.545956 291.310338
10 6144.0 544.118087 248.661056 286.322318
11 6656.0 532.479975 256.000009 286.279570
12 7168.0 507.469040 259.867079 285.767449
13 7680.0 481.253256 262.564106 276.341823
14 8192.0 463.698115 264.970349 284.115618
15 8704.0 416.958106 267.815384 284.987724
16 9216.0 430.319054 270.727053 287.251954
17 9728.0 438.857162 280.278512 289.667485
18 10240.0 447.650282 286.100109 288.112552
19 10752.0 432.241202 246.229020 289.941565
20 11264.0 429.786952 245.760001 286.980888
21 11776.0 423.089806 248.788725 288.391833
22 12288.0 419.504980 254.453844 294.764603
23 12800.0 414.016170 253.047766 288.450715
24 13312.0 411.711355 252.161013 290.443638
25 13824.0 406.090579 256.792581 292.056329
26 14336.0 394.116833 254.485198 287.198654
27 14848.0 384.414233 257.665934 290.188916
28 15360.0 375.015246 257.790220 285.104419
29 15872.0 366.629453 261.986243 290.784741
11 6656.0 527.207907 256.000009 286.793541
12 7168.0 507.469040 261.844750 288.644296
13 7680.0 482.513091 260.707203 277.172933
14 8192.0 460.440290 268.957600 286.183409
15 8704.0 416.958106 267.472468 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 286.433562 289.811322
19 10752.0 430.079980 246.464170 290.267711
20 11264.0 429.104745 245.091565 285.767446
21 11776.0 421.198220 249.447482 288.686414
22 12288.0 420.102570 254.453844 294.911986
23 12800.0 415.135142 253.465340 288.180121
24 13312.0 412.242569 252.559690 290.179836
25 13824.0 405.098897 257.390218 292.571423
26 14336.0 397.761846 254.673567 286.481278
27 14848.0 383.999990 257.293872 289.246765
28 15360.0 374.253788 257.610071 286.433562
29 15872.0 366.982663 262.708969 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 11.478 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.337 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>12:36.772</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:49.502</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>05:21.527</p></td>
<td><p>05:27.659</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>03:21.826</p></td>
<td><p>03:23.673</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>02:11.478</p></td>
<td><p>02:12.337</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>01:41.931</p></td>
<td><p>01:45.823</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>