gaspersic/triton
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[GH-PAGES] Updated website

Browse Source
This commit is contained in:
Philippe Tillet
2022-07-30 00:47:48 +00:00
parent d2acaf2b1e
commit 0c21947b50
165 changed files with 258 additions and 258 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
v1.1.2/getting-started/tutorials/01-vector-add.html
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 31.999999
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 41.626 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 38.377 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>

14
v1.1.2/getting-started/tutorials/02-fused-softmax.html
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 188.321838
0 256.0 512.000001 546.133347 6.756288
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 12160.0 814.058574 406.179533 198.936606
94 12288.0 814.111783 415.222812 199.298541
95 12416.0 812.498981 412.149375 198.854847
96 12544.0 812.566838 412.971190 199.209928
97 12672.0 812.633240 412.097543 199.264875
93 12160.0 814.058574 406.179533 198.631953
94 12288.0 814.111783 415.661740 198.995960
95 12416.0 812.498981 411.722274 198.655991
96 12544.0 812.566838 412.546756 198.815254
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 22.324 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 22.011 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>

58
v1.1.2/getting-started/tutorials/03-matrix-multiplication.html
View File

@@ -569,41 +569,41 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
<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 2.730667 ... 3.276800 2.978909
1 384.0 7.372800 ... 8.507077 7.899428
1 384.0 7.372800 ... 8.507077 8.507077
2 512.0 14.563555 ... 16.384000 16.384000
3 640.0 22.260869 ... 24.380953 24.380953
4 768.0 32.768000 ... 35.389441 34.028308
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 51.150050 ... 53.773130 52.428801
7 1152.0 44.566925 ... 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 69.120002 ... 70.530615 70.530615
14 2048.0 73.908442 ... 77.314362 76.959706
15 2176.0 83.500614 ... 85.632545 85.632545
16 2304.0 68.251065 ... 76.809875 76.809875
17 2432.0 71.305746 ... 74.918570 84.115159
18 2560.0 78.019048 ... 81.512437 80.709358
19 2688.0 83.922689 ... 89.888756 89.464755
20 2816.0 79.154642 ... 82.602666 82.602666
21 2944.0 80.510553 ... 82.305584 81.967162
22 3072.0 81.943708 ... 88.542777 88.197981
23 3200.0 84.432717 ... 95.167286 95.309011
24 3328.0 83.323259 ... 84.695641 84.496824
25 3456.0 80.986004 ... 87.632137 90.180725
26 3584.0 87.127323 ... 94.548254 90.095580
27 3712.0 84.017953 ... 86.528661 85.822459
28 3840.0 84.679936 ... 91.322872 88.615388
29 3968.0 92.864488 ... 81.025193 80.971427
30 4096.0 92.500158 ... 85.325956 84.254693
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 ... 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 ... 72.512412 72.047592
13 1920.0 69.467336 ... 70.892307 70.530615
14 2048.0 74.235468 ... 77.314362 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 ... 83.614477 84.877538
18 2560.0 77.833728 ... 81.512437 81.108913
19 2688.0 83.552988 ... 89.464755 89.888756
20 2816.0 81.067298 ... 83.233226 82.602666
21 2944.0 82.102191 ... 82.784108 82.921853
22 3072.0 81.707223 ... 86.315709 88.197981
23 3200.0 84.210524 ... 94.955488 95.451158
24 3328.0 82.653612 ... 82.275764 84.695641
25 3456.0 80.945348 ... 91.046379 91.097818
26 3584.0 85.106854 ... 90.367227 96.475743
27 3712.0 85.528545 ... 87.783251 87.475786
28 3840.0 82.716526 ... 86.400002 91.701494
29 3968.0 85.811488 ... 91.678389 83.690893
30 4096.0 93.792965 ... 89.418872 87.324485
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 7.140 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 24.601 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>

52
v1.1.2/getting-started/tutorials/05-layer-norm.html
View File

@@ -195,35 +195,35 @@ to download the full example code</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
1 1536.0 351.085717 133.083026 338.201833
2 2048.0 423.724127 162.217818 327.679984
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 290.683877
10 6144.0 544.118087 248.661056 285.767458
11 6656.0 527.207907 256.410903 286.793541
12 7168.0 507.469040 262.243907 288.644296
13 7680.0 482.513091 260.707203 277.590365
3 2560.0 461.954908 182.857144 325.079368
4 3072.0 511.999982 191.501303 319.168834
5 3584.0 554.941930 208.271186 309.410081
6 4096.0 568.231237 220.412561 299.707322
7 4608.0 498.162157 231.849059 286.507772
8 5120.0 525.128191 242.845844 283.787523
9 5632.0 538.517949 243.107920 291.310338
10 6144.0 544.118087 248.661056 285.214712
11 6656.0 527.207907 256.000009 286.793541
12 7168.0 507.469040 262.243907 288.160801
13 7680.0 482.513091 260.707203 273.471806
14 8192.0 460.440290 269.326017 286.600589
15 8704.0 416.958106 267.815384 284.987724
16 9216.0 428.651187 273.066667 289.507855
17 9728.0 439.683593 280.615388 288.950501
18 10240.0 447.650282 286.767793 289.811322
19 10752.0 430.079980 246.464170 290.267711
20 11264.0 429.104745 245.091565 285.767446
21 11776.0 421.826879 249.447482 288.686414
16 9216.0 428.651187 272.729961 289.507855
17 9728.0 438.857162 280.615388 289.308559
18 10240.0 447.650282 286.433562 288.112552
19 10752.0 429.364408 245.994291 290.267711
20 11264.0 429.104745 245.091565 286.069848
21 11776.0 421.826879 248.569911 288.686414
22 12288.0 420.102570 254.453844 295.207195
23 12800.0 415.696898 253.674644 288.450715
24 13312.0 412.242569 252.759501 290.179836
25 13824.0 405.594132 257.390218 292.571423
26 14336.0 397.761846 254.862216 286.481278
27 14848.0 384.414233 257.293872 289.246765
28 15360.0 374.253788 257.790220 286.433562
29 15872.0 366.982663 262.708969 291.229369
23 12800.0 415.696898 253.047766 288.450715
24 13312.0 412.775186 252.759501 290.179836
25 13824.0 405.098897 256.991469 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 285.546077
29 15872.0 367.336555 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 12.370 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.501 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>

10
v1.1.2/getting-started/tutorials/sg_execution_times.html
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>12:23.470</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>12:36.500</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>05:07.140</p></td>
<td><p>05:24.601</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>03:22.324</p></td>
<td><p>03:22.011</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>02:12.370</p></td>
<td><p>02:11.501</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>01:41.626</p></td>
<td><p>01:38.377</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>