[GH-PAGES] Updated website
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@@ -233,8 +233,8 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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size Triton Torch
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@@ -254,7 +254,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
|
||||
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||||
.. rst-class:: sphx-glr-timing
|
||||
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**Total running time of the script:** ( 0 minutes 11.055 seconds)
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**Total running time of the script:** ( 0 minutes 10.981 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
|
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@@ -302,15 +302,15 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
|
||||
N Triton Torch (native) Torch (jit)
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[98 rows x 4 columns]
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@@ -329,7 +329,7 @@ In the above plot, we can see that:
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|
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.. rst-class:: sphx-glr-timing
|
||||
|
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**Total running time of the script:** ( 1 minutes 13.186 seconds)
|
||||
**Total running time of the script:** ( 1 minutes 12.654 seconds)
|
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|
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
|
||||
|
@@ -483,37 +483,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
|
||||
matmul-performance:
|
||||
M cuBLAS ... Triton Triton (+ LeakyReLU)
|
||||
0 128.0 0.455111 ... 0.512000 0.512000
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1 256.0 2.978909 ... 2.978909 2.978909
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|
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|
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||||
|
||||
[32 rows x 5 columns]
|
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|
||||
@@ -523,7 +523,7 @@ 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 30.425 seconds)
|
||||
**Total running time of the script:** ( 2 minutes 30.126 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
|
||||
|
@@ -5,12 +5,12 @@
|
||||
|
||||
Computation times
|
||||
=================
|
||||
**03:54.665** total execution time for **getting-started_tutorials** files:
|
||||
**03:53.760** total execution time for **getting-started_tutorials** files:
|
||||
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:30.425 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:30.126 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:13.186 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.654 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.055 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:10.981 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
|
@@ -321,8 +321,8 @@ for different problem sizes.</p>
|
||||
size Triton Torch
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5 131072.0 219.428568 219.428568
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6 262144.0 341.333321 384.000001
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@@ -337,7 +337,7 @@ for different problem sizes.</p>
|
||||
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 11.055 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 10.981 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>
|
||||
|
@@ -387,15 +387,15 @@ We will then compare its performance against (1) <code class="code docutils lite
|
||||
N Triton Torch (native) Torch (jit)
|
||||
0 256.0 512.000001 546.133347 186.181817
|
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1 384.0 585.142862 585.142862 153.600004
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2 512.0 630.153853 606.814814 154.566038
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3 640.0 660.645170 640.000002 160.000000
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2 512.0 630.153853 585.142849 154.566038
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3 640.0 682.666684 640.000002 160.000000
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4 768.0 702.171410 664.216187 163.839992
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.. ... ... ... ...
|
||||
93 12160.0 812.359066 406.179533 199.038365
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||||
94 12288.0 812.429770 415.222812 199.298541
|
||||
93 12160.0 812.359066 405.755985 198.936606
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||||
94 12288.0 812.429770 415.661740 199.197579
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95 12416.0 810.840807 412.149375 198.854847
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96 12544.0 810.925276 412.971190 199.209928
|
||||
97 12672.0 809.389265 412.097543 199.167004
|
||||
96 12544.0 810.925276 412.971190 199.111113
|
||||
97 12672.0 811.007961 412.097543 199.167004
|
||||
|
||||
[98 rows x 4 columns]
|
||||
</pre></div>
|
||||
@@ -409,7 +409,7 @@ This means that – when temporary data is too large to fit entirely in the GPU
|
||||
Note that our Triton kernel is not only faster than PyTorch’s CUDA kernel, it is also <strong>easier to read, understand and maintain</strong>.</p></li>
|
||||
</ul>
|
||||
</div></blockquote>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 13.186 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 12.654 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>
|
||||
|
@@ -581,42 +581,42 @@ 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)
|
||||
0 128.0 0.455111 ... 0.512000 0.512000
|
||||
1 256.0 2.978909 ... 2.978909 2.978909
|
||||
2 384.0 7.372800 ... 8.507077 7.899428
|
||||
1 256.0 2.730667 ... 3.276800 2.978909
|
||||
2 384.0 7.372800 ... 8.507077 8.507077
|
||||
3 512.0 14.563555 ... 16.384000 15.420235
|
||||
4 640.0 22.260869 ... 24.380953 24.380953
|
||||
5 768.0 32.768000 ... 34.028308 34.028308
|
||||
6 896.0 39.025776 ... 39.025776 35.123201
|
||||
6 896.0 39.025776 ... 40.140799 35.123201
|
||||
7 1024.0 49.932191 ... 52.428801 52.428801
|
||||
8 1152.0 44.566925 ... 46.656000 46.656000
|
||||
9 1280.0 51.200001 ... 56.888887 56.109587
|
||||
10 1408.0 64.138541 ... 64.902096 64.902096
|
||||
11 1536.0 78.643199 ... 76.106321 76.106321
|
||||
12 1664.0 62.929456 ... 62.061463 62.061463
|
||||
8 1152.0 44.566925 ... 46.656000 45.938215
|
||||
9 1280.0 51.200001 ... 56.109587 56.109587
|
||||
10 1408.0 64.138541 ... 64.902096 64.138541
|
||||
11 1536.0 80.430545 ... 76.106321 75.296679
|
||||
12 1664.0 63.372618 ... 62.492442 62.061463
|
||||
13 1792.0 72.983276 ... 69.810085 69.379162
|
||||
14 1920.0 67.764707 ... 70.530615 70.530615
|
||||
15 2048.0 73.908442 ... 75.234154 74.898285
|
||||
16 2176.0 83.500614 ... 81.143743 81.143743
|
||||
17 2304.0 68.446623 ... 73.501144 73.501144
|
||||
18 2432.0 71.305746 ... 82.147552 82.147552
|
||||
19 2560.0 77.833728 ... 77.283019 77.101175
|
||||
20 2688.0 81.053536 ... 81.928846 83.922689
|
||||
21 2816.0 81.981598 ... 79.443003 80.320825
|
||||
22 2944.0 82.373605 ... 77.385141 78.112900
|
||||
23 3072.0 81.472093 ... 83.761985 79.638683
|
||||
24 3200.0 84.768213 ... 88.888888 85.561498
|
||||
25 3328.0 83.905938 ... 87.794262 87.156532
|
||||
26 3456.0 80.220468 ... 85.676480 84.068369
|
||||
27 3584.0 86.707226 ... 95.553020 94.847460
|
||||
28 3712.0 83.247783 ... 84.303780 85.309435
|
||||
29 3840.0 80.255442 ... 83.339866 85.005380
|
||||
30 3968.0 88.938731 ... 87.409694 87.159957
|
||||
31 4096.0 91.616198 ... 89.597949 89.538177
|
||||
14 1920.0 68.435645 ... 67.764707 69.818184
|
||||
15 2048.0 73.584279 ... 75.234154 74.898285
|
||||
16 2176.0 83.500614 ... 81.143743 78.916269
|
||||
17 2304.0 68.056616 ... 73.501144 73.051599
|
||||
18 2432.0 71.125224 ... 80.269900 80.963875
|
||||
19 2560.0 77.833728 ... 76.920185 76.382283
|
||||
20 2688.0 80.027544 ... 79.524227 82.284288
|
||||
21 2816.0 83.392363 ... 79.587973 76.785575
|
||||
22 2944.0 82.509987 ... 79.230573 79.993627
|
||||
23 3072.0 81.589488 ... 83.761985 82.301023
|
||||
24 3200.0 84.768213 ... 89.385477 89.012517
|
||||
25 3328.0 80.617354 ... 80.707733 86.217120
|
||||
26 3456.0 81.518272 ... 85.223646 82.183044
|
||||
27 3584.0 84.033077 ... 93.564405 95.047985
|
||||
28 3712.0 86.267139 ... 88.015279 89.194055
|
||||
29 3840.0 84.874902 ... 88.402879 87.217666
|
||||
30 3968.0 92.442373 ... 87.850207 87.347124
|
||||
31 4096.0 93.531519 ... 85.926841 85.871865
|
||||
|
||||
[32 rows x 5 columns]
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 30.425 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 30.126 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>03:54.665</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>03:53.760</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>02:30.425</p></td>
|
||||
<td><p>02:30.126</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>01:13.186</p></td>
|
||||
<td><p>01:12.654</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>00:11.055</p></td>
|
||||
<td><p>00:10.981</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
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||||
</tbody>
|
||||
|