[GH-PAGES] Updated website
Before Width: | Height: | Size: 24 KiB After Width: | Height: | Size: 24 KiB |
Before Width: | Height: | Size: 15 KiB After Width: | Height: | Size: 15 KiB |
Before Width: | Height: | Size: 37 KiB After Width: | Height: | Size: 38 KiB |
Before Width: | Height: | Size: 24 KiB After Width: | Height: | Size: 24 KiB |
Before Width: | Height: | Size: 55 KiB After Width: | Height: | Size: 55 KiB |
Before Width: | Height: | Size: 32 KiB After Width: | Height: | Size: 32 KiB |
@@ -231,20 +231,20 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
|
||||
|
||||
vector-add-performance:
|
||||
size Triton Torch
|
||||
0 4096.0 8.041885 9.600000
|
||||
1 8192.0 15.999999 19.200000
|
||||
2 16384.0 38.400001 38.400001
|
||||
3 32768.0 76.800002 76.800002
|
||||
0 4096.0 9.540372 9.600000
|
||||
1 8192.0 19.200000 19.200000
|
||||
2 16384.0 38.400001 31.999999
|
||||
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
|
||||
7 524288.0 472.615390 472.615390
|
||||
8 1048576.0 614.400016 614.400016
|
||||
9 2097152.0 722.823517 722.823517
|
||||
9 2097152.0 722.823517 702.171410
|
||||
10 4194304.0 780.190482 780.190482
|
||||
11 8388608.0 812.429770 812.429770
|
||||
12 16777216.0 833.084721 833.084721
|
||||
13 33554432.0 843.811163 842.004273
|
||||
13 33554432.0 843.811163 843.811163
|
||||
14 67108864.0 849.278610 848.362445
|
||||
15 134217728.0 851.577704 850.656574
|
||||
|
||||
@@ -254,7 +254,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
|
||||
|
||||
.. rst-class:: sphx-glr-timing
|
||||
|
||||
**Total running time of the script:** ( 0 minutes 10.979 seconds)
|
||||
**Total running time of the script:** ( 0 minutes 10.991 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
|
||||
|
@@ -300,17 +300,17 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
|
||||
|
||||
softmax-performance:
|
||||
N Triton Torch (native) Torch (jit)
|
||||
0 256.0 512.000001 512.000001 190.511628
|
||||
1 384.0 585.142862 585.142862 151.703707
|
||||
2 512.0 630.153853 606.814814 154.566038
|
||||
0 256.0 512.000001 546.133347 186.181817
|
||||
1 384.0 585.142862 585.142862 153.600004
|
||||
2 512.0 630.153853 606.814814 156.038096
|
||||
3 640.0 660.645170 640.000002 160.000000
|
||||
4 768.0 702.171410 664.216187 163.839992
|
||||
.. ... ... ... ...
|
||||
93 12160.0 812.359066 405.755985 199.038365
|
||||
93 12160.0 812.359066 406.179533 199.038365
|
||||
94 12288.0 812.429770 415.661740 199.298541
|
||||
95 12416.0 810.840807 411.722274 198.954424
|
||||
95 12416.0 810.840807 412.149375 198.854847
|
||||
96 12544.0 810.925276 412.971190 199.111113
|
||||
97 12672.0 809.389265 412.516771 199.264875
|
||||
97 12672.0 811.007961 412.097543 199.264875
|
||||
|
||||
[98 rows x 4 columns]
|
||||
|
||||
@@ -328,7 +328,7 @@ In the above plot, we can see that:
|
||||
|
||||
.. rst-class:: sphx-glr-timing
|
||||
|
||||
**Total running time of the script:** ( 1 minutes 12.611 seconds)
|
||||
**Total running time of the script:** ( 1 minutes 12.603 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
|
||||
|
@@ -462,37 +462,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
|
||||
|
||||
matmul-performance:
|
||||
M cuBLAS ... Triton Triton (+ LeakyReLU)
|
||||
0 256.0 2.730667 ... 3.276800 3.276800
|
||||
1 384.0 7.372800 ... 8.507077 8.507077
|
||||
2 512.0 14.563555 ... 15.420235 15.420235
|
||||
0 256.0 2.730667 ... 3.276800 2.978909
|
||||
1 384.0 7.372800 ... 7.899428 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 ... 35.389441 34.028308
|
||||
4 768.0 32.768000 ... 34.028308 34.028308
|
||||
5 896.0 39.025776 ... 40.140799 39.025776
|
||||
6 1024.0 49.932191 ... 52.428801 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 ... 64.902096 64.902096
|
||||
10 1536.0 80.430545 ... 76.933564 75.296679
|
||||
11 1664.0 63.372618 ... 61.636381 61.636381
|
||||
12 1792.0 72.983276 ... 69.810085 69.379162
|
||||
13 1920.0 69.120002 ... 69.120002 67.106797
|
||||
14 2048.0 73.584279 ... 74.898285 68.200062
|
||||
15 2176.0 82.813365 ... 80.817862 78.302130
|
||||
16 2304.0 68.251065 ... 73.728002 73.275679
|
||||
17 2432.0 71.305746 ... 79.139336 80.499895
|
||||
18 2560.0 77.649287 ... 77.283019 76.382283
|
||||
19 2688.0 80.880718 ... 82.823267 84.295681
|
||||
20 2816.0 78.868366 ... 78.161663 79.154642
|
||||
21 2944.0 80.380696 ... 80.122235 77.385141
|
||||
22 3072.0 81.355034 ... 83.638266 82.782312
|
||||
23 3200.0 82.901554 ... 87.551302 89.510493
|
||||
24 3328.0 81.438120 ... 80.798314 84.596116
|
||||
25 3456.0 81.683457 ... 85.494768 85.676480
|
||||
26 3584.0 86.457107 ... 95.148565 89.201778
|
||||
27 3712.0 85.163978 ... 81.883070 83.596102
|
||||
28 3840.0 84.485870 ... 87.562949 87.355452
|
||||
29 3968.0 93.076994 ... 83.635320 83.463707
|
||||
30 4096.0 93.531519 ... 90.382307 90.321484
|
||||
10 1536.0 78.643199 ... 76.106321 76.106321
|
||||
11 1664.0 63.372618 ... 62.061463 62.061463
|
||||
12 1792.0 72.983276 ... 69.810085 69.810085
|
||||
13 1920.0 69.120002 ... 70.172588 70.172588
|
||||
14 2048.0 73.584279 ... 74.898285 74.565406
|
||||
15 2176.0 82.137338 ... 80.817862 78.916269
|
||||
16 2304.0 67.863272 ... 73.501144 73.275679
|
||||
17 2432.0 71.125224 ... 79.813818 81.197876
|
||||
18 2560.0 77.649287 ... 77.283019 77.283019
|
||||
19 2688.0 80.196737 ... 83.922689 80.708630
|
||||
20 2816.0 81.827785 ... 77.330158 79.298560
|
||||
21 2944.0 82.237674 ... 79.104810 77.145564
|
||||
22 3072.0 82.540970 ... 82.903517 83.391907
|
||||
23 3200.0 84.768213 ... 87.551302 89.761569
|
||||
24 3328.0 80.707733 ... 84.298943 87.580655
|
||||
25 3456.0 81.849303 ... 84.775569 84.954233
|
||||
26 3584.0 86.707226 ... 94.647779 94.947616
|
||||
27 3712.0 83.317214 ... 84.159518 82.357725
|
||||
28 3840.0 84.292684 ... 87.493673 87.355452
|
||||
29 3968.0 92.302520 ... 88.103928 87.976885
|
||||
30 4096.0 93.596744 ... 90.443212 90.382307
|
||||
|
||||
[31 rows x 5 columns]
|
||||
|
||||
@@ -502,7 +502,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
|
||||
|
||||
.. rst-class:: sphx-glr-timing
|
||||
|
||||
**Total running time of the script:** ( 2 minutes 11.445 seconds)
|
||||
**Total running time of the script:** ( 2 minutes 8.434 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
|
||||
|
@@ -5,12 +5,12 @@
|
||||
|
||||
Computation times
|
||||
=================
|
||||
**03:35.035** total execution time for **getting-started_tutorials** files:
|
||||
**03:32.028** total execution time for **getting-started_tutorials** files:
|
||||
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:11.445 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:08.434 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.611 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.603 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:10.979 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:10.991 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
|
@@ -319,25 +319,25 @@ for different problem sizes.</p>
|
||||
<p class="sphx-glr-script-out">Out:</p>
|
||||
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector-add-performance:
|
||||
size Triton Torch
|
||||
0 4096.0 8.041885 9.600000
|
||||
1 8192.0 15.999999 19.200000
|
||||
2 16384.0 38.400001 38.400001
|
||||
3 32768.0 76.800002 76.800002
|
||||
0 4096.0 9.540372 9.600000
|
||||
1 8192.0 19.200000 19.200000
|
||||
2 16384.0 38.400001 31.999999
|
||||
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
|
||||
7 524288.0 472.615390 472.615390
|
||||
8 1048576.0 614.400016 614.400016
|
||||
9 2097152.0 722.823517 722.823517
|
||||
9 2097152.0 722.823517 702.171410
|
||||
10 4194304.0 780.190482 780.190482
|
||||
11 8388608.0 812.429770 812.429770
|
||||
12 16777216.0 833.084721 833.084721
|
||||
13 33554432.0 843.811163 842.004273
|
||||
13 33554432.0 843.811163 843.811163
|
||||
14 67108864.0 849.278610 848.362445
|
||||
15 134217728.0 851.577704 850.656574
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 10.979 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 10.991 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>
|
||||
|
@@ -385,17 +385,17 @@ 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 512.000001 190.511628
|
||||
1 384.0 585.142862 585.142862 151.703707
|
||||
2 512.0 630.153853 606.814814 154.566038
|
||||
0 256.0 512.000001 546.133347 186.181817
|
||||
1 384.0 585.142862 585.142862 153.600004
|
||||
2 512.0 630.153853 606.814814 156.038096
|
||||
3 640.0 660.645170 640.000002 160.000000
|
||||
4 768.0 702.171410 664.216187 163.839992
|
||||
.. ... ... ... ...
|
||||
93 12160.0 812.359066 405.755985 199.038365
|
||||
93 12160.0 812.359066 406.179533 199.038365
|
||||
94 12288.0 812.429770 415.661740 199.298541
|
||||
95 12416.0 810.840807 411.722274 198.954424
|
||||
95 12416.0 810.840807 412.149375 198.854847
|
||||
96 12544.0 810.925276 412.971190 199.111113
|
||||
97 12672.0 809.389265 412.516771 199.264875
|
||||
97 12672.0 811.007961 412.097543 199.264875
|
||||
|
||||
[98 rows x 4 columns]
|
||||
</pre></div>
|
||||
@@ -408,7 +408,7 @@ 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> ( 1 minutes 12.611 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 12.603 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>
|
||||
|
@@ -566,42 +566,42 @@ 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 2.730667 ... 3.276800 3.276800
|
||||
1 384.0 7.372800 ... 8.507077 8.507077
|
||||
2 512.0 14.563555 ... 15.420235 15.420235
|
||||
0 256.0 2.730667 ... 3.276800 2.978909
|
||||
1 384.0 7.372800 ... 7.899428 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 ... 35.389441 34.028308
|
||||
4 768.0 32.768000 ... 34.028308 34.028308
|
||||
5 896.0 39.025776 ... 40.140799 39.025776
|
||||
6 1024.0 49.932191 ... 52.428801 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 ... 64.902096 64.902096
|
||||
10 1536.0 80.430545 ... 76.933564 75.296679
|
||||
11 1664.0 63.372618 ... 61.636381 61.636381
|
||||
12 1792.0 72.983276 ... 69.810085 69.379162
|
||||
13 1920.0 69.120002 ... 69.120002 67.106797
|
||||
14 2048.0 73.584279 ... 74.898285 68.200062
|
||||
15 2176.0 82.813365 ... 80.817862 78.302130
|
||||
16 2304.0 68.251065 ... 73.728002 73.275679
|
||||
17 2432.0 71.305746 ... 79.139336 80.499895
|
||||
18 2560.0 77.649287 ... 77.283019 76.382283
|
||||
19 2688.0 80.880718 ... 82.823267 84.295681
|
||||
20 2816.0 78.868366 ... 78.161663 79.154642
|
||||
21 2944.0 80.380696 ... 80.122235 77.385141
|
||||
22 3072.0 81.355034 ... 83.638266 82.782312
|
||||
23 3200.0 82.901554 ... 87.551302 89.510493
|
||||
24 3328.0 81.438120 ... 80.798314 84.596116
|
||||
25 3456.0 81.683457 ... 85.494768 85.676480
|
||||
26 3584.0 86.457107 ... 95.148565 89.201778
|
||||
27 3712.0 85.163978 ... 81.883070 83.596102
|
||||
28 3840.0 84.485870 ... 87.562949 87.355452
|
||||
29 3968.0 93.076994 ... 83.635320 83.463707
|
||||
30 4096.0 93.531519 ... 90.382307 90.321484
|
||||
10 1536.0 78.643199 ... 76.106321 76.106321
|
||||
11 1664.0 63.372618 ... 62.061463 62.061463
|
||||
12 1792.0 72.983276 ... 69.810085 69.810085
|
||||
13 1920.0 69.120002 ... 70.172588 70.172588
|
||||
14 2048.0 73.584279 ... 74.898285 74.565406
|
||||
15 2176.0 82.137338 ... 80.817862 78.916269
|
||||
16 2304.0 67.863272 ... 73.501144 73.275679
|
||||
17 2432.0 71.125224 ... 79.813818 81.197876
|
||||
18 2560.0 77.649287 ... 77.283019 77.283019
|
||||
19 2688.0 80.196737 ... 83.922689 80.708630
|
||||
20 2816.0 81.827785 ... 77.330158 79.298560
|
||||
21 2944.0 82.237674 ... 79.104810 77.145564
|
||||
22 3072.0 82.540970 ... 82.903517 83.391907
|
||||
23 3200.0 84.768213 ... 87.551302 89.761569
|
||||
24 3328.0 80.707733 ... 84.298943 87.580655
|
||||
25 3456.0 81.849303 ... 84.775569 84.954233
|
||||
26 3584.0 86.707226 ... 94.647779 94.947616
|
||||
27 3712.0 83.317214 ... 84.159518 82.357725
|
||||
28 3840.0 84.292684 ... 87.493673 87.355452
|
||||
29 3968.0 92.302520 ... 88.103928 87.976885
|
||||
30 4096.0 93.596744 ... 90.443212 90.382307
|
||||
|
||||
[31 rows x 5 columns]
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.445 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 8.434 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>
|
||||
|
@@ -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>03:35.035</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>03:32.028</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<table class="docutils align-default">
|
||||
<colgroup>
|
||||
<col style="width: 85%" />
|
||||
@@ -183,15 +183,15 @@
|
||||
</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>02:11.445</p></td>
|
||||
<td><p>02:08.434</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>01:12.611</p></td>
|
||||
<td><p>01:12.603</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-odd"><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>00:10.979</p></td>
|
||||
<td><p>00:10.991</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
|