[GH-PAGES] Updated website
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@@ -234,10 +234,10 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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9 2097152.0 722.823517 722.823517
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@@ -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 11.059 seconds)
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**Total running time of the script:** ( 0 minutes 11.046 seconds)
|
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
|
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@@ -288,15 +288,15 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
|
||||
N Triton Torch (native) Torch (jit)
|
||||
0 256.0 512.000001 546.133347 186.181817
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.. ... ... ... ...
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|
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||||
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97 12672.0 806.170993 412.097543 199.264875
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95 12416.0 809.189387 412.149375 198.954424
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96 12544.0 807.661970 412.546756 199.209928
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97 12672.0 807.776923 412.097543 199.167004
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[98 rows x 4 columns]
|
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@@ -314,7 +314,7 @@ 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 12.645 seconds)
|
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**Total running time of the script:** ( 1 minutes 12.659 seconds)
|
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|
||||
.. _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 ... 7.899428 7.899428
|
||||
0 256.0 2.978909 ... 2.978909 2.978909
|
||||
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 ... 34.028308 34.028308
|
||||
5 896.0 39.025776 ... 40.140799 39.025776
|
||||
5 896.0 39.025776 ... 39.025776 39.025776
|
||||
6 1024.0 49.932191 ... 53.773130 52.428801
|
||||
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|
||||
8 1280.0 51.200001 ... 56.888887 56.888887
|
||||
9 1408.0 64.138541 ... 67.305878 59.909625
|
||||
10 1536.0 79.526831 ... 78.643199 78.643199
|
||||
7 1152.0 44.566925 ... 46.656000 45.938215
|
||||
8 1280.0 51.200001 ... 56.109587 56.109587
|
||||
9 1408.0 64.138541 ... 66.485074 59.909625
|
||||
10 1536.0 79.526831 ... 79.526831 78.643199
|
||||
11 1664.0 63.372618 ... 62.492442 62.492442
|
||||
12 1792.0 72.983276 ... 72.047592 72.047592
|
||||
13 1920.0 67.764707 ... 70.172588 70.172588
|
||||
14 2048.0 73.584279 ... 76.608294 76.608294
|
||||
15 2176.0 83.155572 ... 81.472263 83.848535
|
||||
12 1792.0 72.983276 ... 72.512412 72.512412
|
||||
13 1920.0 65.828572 ... 70.530615 70.172588
|
||||
14 2048.0 73.908442 ... 76.608294 76.608294
|
||||
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|
||||
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|
||||
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|
||||
18 2560.0 78.019048 ... 81.310171 81.108913
|
||||
19 2688.0 83.186525 ... 88.628636 89.044730
|
||||
20 2816.0 81.521884 ... 82.446516 80.617762
|
||||
21 2944.0 81.832567 ... 82.373605 81.564701
|
||||
22 3072.0 82.540970 ... 86.712254 88.335577
|
||||
23 3200.0 84.993363 ... 88.275863 92.352095
|
||||
24 3328.0 83.808259 ... 85.096096 84.695641
|
||||
25 3456.0 81.766291 ... 91.097818 88.400840
|
||||
26 3584.0 87.296493 ... 97.311031 94.152243
|
||||
27 3712.0 84.230479 ... 88.640059 83.947349
|
||||
28 3840.0 81.198237 ... 85.005380 87.355452
|
||||
29 3968.0 91.472214 ... 89.789505 89.921841
|
||||
30 4096.0 93.466385 ... 92.182504 92.056052
|
||||
17 2432.0 71.305746 ... 73.738752 83.366361
|
||||
18 2560.0 77.649287 ... 80.117359 80.313727
|
||||
19 2688.0 83.922689 ... 84.861423 88.422041
|
||||
20 2816.0 83.392363 ... 82.446516 81.369790
|
||||
21 2944.0 79.737653 ... 81.564701 82.509987
|
||||
22 3072.0 81.707223 ... 88.197981 88.890270
|
||||
23 3200.0 83.989503 ... 88.765601 94.955488
|
||||
24 3328.0 81.530349 ... 84.596116 84.496824
|
||||
25 3456.0 81.518272 ... 91.200871 86.503829
|
||||
26 3584.0 87.381330 ... 97.205829 89.290361
|
||||
27 3712.0 85.822459 ... 84.730571 83.947349
|
||||
28 3840.0 82.840447 ... 89.187096 91.473945
|
||||
29 3968.0 92.442373 ... 91.540836 91.335278
|
||||
30 4096.0 93.792965 ... 93.336389 93.142072
|
||||
|
||||
[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 20.037 seconds)
|
||||
**Total running time of the script:** ( 2 minutes 14.528 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
|
||||
|
@@ -5,14 +5,14 @@
|
||||
|
||||
Computation times
|
||||
=================
|
||||
**03:43.927** total execution time for **getting-started_tutorials** files:
|
||||
**03:38.419** total execution time for **getting-started_tutorials** files:
|
||||
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:20.037 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:14.528 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.645 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.659 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.059 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.046 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.186 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
|
@@ -323,10 +323,10 @@ 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 76.800002 76.800002
|
||||
3 32768.0 63.999998 76.800002
|
||||
4 65536.0 127.999995 127.999995
|
||||
5 131072.0 219.428568 219.428568
|
||||
6 262144.0 341.333321 341.333321
|
||||
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
|
||||
@@ -338,7 +338,7 @@ 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> ( 0 minutes 11.059 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 11.046 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>
|
||||
|
@@ -375,15 +375,15 @@ 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
|
||||
1 384.0 585.142862 585.142862 153.600004
|
||||
2 512.0 630.153853 585.142849 156.038096
|
||||
3 640.0 682.666684 640.000002 160.000000
|
||||
2 512.0 630.153853 606.814814 154.566038
|
||||
3 640.0 660.645170 640.000002 160.000000
|
||||
4 768.0 702.171410 664.216187 163.839992
|
||||
.. ... ... ... ...
|
||||
93 12160.0 810.666687 406.179533 199.038365
|
||||
94 12288.0 810.754644 415.222812 199.298541
|
||||
95 12416.0 809.189387 411.722274 198.954424
|
||||
96 12544.0 807.661970 412.971190 199.209928
|
||||
97 12672.0 806.170993 412.097543 199.264875
|
||||
94 12288.0 810.754644 415.661740 199.298541
|
||||
95 12416.0 809.189387 412.149375 198.954424
|
||||
96 12544.0 807.661970 412.546756 199.209928
|
||||
97 12672.0 807.776923 412.097543 199.167004
|
||||
|
||||
[98 rows x 4 columns]
|
||||
</pre></div>
|
||||
@@ -396,7 +396,7 @@ 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 12.645 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 12.659 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>
|
||||
|
@@ -567,42 +567,42 @@ 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 ... 7.899428 7.899428
|
||||
0 256.0 2.978909 ... 2.978909 2.978909
|
||||
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 ... 34.028308 34.028308
|
||||
5 896.0 39.025776 ... 40.140799 39.025776
|
||||
5 896.0 39.025776 ... 39.025776 39.025776
|
||||
6 1024.0 49.932191 ... 53.773130 52.428801
|
||||
7 1152.0 44.566925 ... 46.656000 46.656000
|
||||
8 1280.0 51.200001 ... 56.888887 56.888887
|
||||
9 1408.0 64.138541 ... 67.305878 59.909625
|
||||
10 1536.0 79.526831 ... 78.643199 78.643199
|
||||
7 1152.0 44.566925 ... 46.656000 45.938215
|
||||
8 1280.0 51.200001 ... 56.109587 56.109587
|
||||
9 1408.0 64.138541 ... 66.485074 59.909625
|
||||
10 1536.0 79.526831 ... 79.526831 78.643199
|
||||
11 1664.0 63.372618 ... 62.492442 62.492442
|
||||
12 1792.0 72.983276 ... 72.047592 72.047592
|
||||
13 1920.0 67.764707 ... 70.172588 70.172588
|
||||
14 2048.0 73.584279 ... 76.608294 76.608294
|
||||
15 2176.0 83.155572 ... 81.472263 83.848535
|
||||
12 1792.0 72.983276 ... 72.512412 72.512412
|
||||
13 1920.0 65.828572 ... 70.530615 70.172588
|
||||
14 2048.0 73.908442 ... 76.608294 76.608294
|
||||
15 2176.0 81.472263 ... 84.909907 84.553145
|
||||
16 2304.0 68.251065 ... 76.809875 76.809875
|
||||
17 2432.0 71.305746 ... 74.719317 85.393507
|
||||
18 2560.0 78.019048 ... 81.310171 81.108913
|
||||
19 2688.0 83.186525 ... 88.628636 89.044730
|
||||
20 2816.0 81.521884 ... 82.446516 80.617762
|
||||
21 2944.0 81.832567 ... 82.373605 81.564701
|
||||
22 3072.0 82.540970 ... 86.712254 88.335577
|
||||
23 3200.0 84.993363 ... 88.275863 92.352095
|
||||
24 3328.0 83.808259 ... 85.096096 84.695641
|
||||
25 3456.0 81.766291 ... 91.097818 88.400840
|
||||
26 3584.0 87.296493 ... 97.311031 94.152243
|
||||
27 3712.0 84.230479 ... 88.640059 83.947349
|
||||
28 3840.0 81.198237 ... 85.005380 87.355452
|
||||
29 3968.0 91.472214 ... 89.789505 89.921841
|
||||
30 4096.0 93.466385 ... 92.182504 92.056052
|
||||
17 2432.0 71.305746 ... 73.738752 83.366361
|
||||
18 2560.0 77.649287 ... 80.117359 80.313727
|
||||
19 2688.0 83.922689 ... 84.861423 88.422041
|
||||
20 2816.0 83.392363 ... 82.446516 81.369790
|
||||
21 2944.0 79.737653 ... 81.564701 82.509987
|
||||
22 3072.0 81.707223 ... 88.197981 88.890270
|
||||
23 3200.0 83.989503 ... 88.765601 94.955488
|
||||
24 3328.0 81.530349 ... 84.596116 84.496824
|
||||
25 3456.0 81.518272 ... 91.200871 86.503829
|
||||
26 3584.0 87.381330 ... 97.205829 89.290361
|
||||
27 3712.0 85.822459 ... 84.730571 83.947349
|
||||
28 3840.0 82.840447 ... 89.187096 91.473945
|
||||
29 3968.0 92.442373 ... 91.540836 91.335278
|
||||
30 4096.0 93.792965 ... 93.336389 93.142072
|
||||
|
||||
[31 rows x 5 columns]
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 20.037 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 14.528 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>03:43.927</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>03:38.419</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>02:20.037</p></td>
|
||||
<td><p>02:14.528</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>01:12.645</p></td>
|
||||
<td><p>01:12.659</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>00:11.059</p></td>
|
||||
<td><p>00:11.046</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-even"><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>
|
||||
|