[GH-PAGES] Updated website
This commit is contained in:
Philippe Tillet
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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: f3d1ccbddb6a63c7385d319834b5692f
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config: 15e6b27e870b3e8bd2987567dc3b7b92
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tags: 645f666f9bcd5a90fca523b33c5a78b7
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@@ -232,19 +232,19 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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vector-add-performance:
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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:** ( 1 minutes 28.027 seconds)
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**Total running time of the script:** ( 1 minutes 43.206 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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@@ -286,17 +286,17 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
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softmax-performance:
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N Triton Torch (native) Torch (jit)
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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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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 3 minutes 19.106 seconds)
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**Total running time of the script:** ( 3 minutes 23.188 seconds)
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
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@@ -463,36 +463,36 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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matmul-performance:
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M cuBLAS ... Triton Triton (+ LeakyReLU)
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[31 rows x 5 columns]
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@@ -502,7 +502,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 26.690 seconds)
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**Total running time of the script:** ( 5 minutes 26.832 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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@@ -238,7 +238,7 @@ References
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 0.372 seconds)
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**Total running time of the script:** ( 0 minutes 0.011 seconds)
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.. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:
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@@ -38,36 +38,36 @@ Layer Normalization
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layer-norm-backward:
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N Triton Torch Apex
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||||
0 1024.0 307.200008 99.096776 307.200008
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
26 14336.0 399.146178 255.809666 289.372589
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||||
27 14848.0 383.586664 256.922861 287.844912
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||||
28 15360.0 376.932517 258.513318 288.225185
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||||
29 15872.0 369.832994 261.267482 290.341468
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||||
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||||
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||||
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@@ -329,7 +329,7 @@ Layer Normalization
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.. rst-class:: sphx-glr-timing
|
||||
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||||
**Total running time of the script:** ( 2 minutes 11.692 seconds)
|
||||
**Total running time of the script:** ( 2 minutes 11.696 seconds)
|
||||
|
||||
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||||
.. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:
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@@ -5,16 +5,16 @@
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Computation times
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||||
=================
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||||
**12:25.887** total execution time for **getting-started_tutorials** files:
|
||||
**12:44.933** total execution time for **getting-started_tutorials** files:
|
||||
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
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||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:26.690 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:26.832 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
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||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:19.106 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:23.188 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 02:11.692 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 02:11.696 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:28.027 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:43.206 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.372 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.011 | 0.0 MB |
|
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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@@ -322,24 +322,24 @@ for different problem sizes.</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector-add-performance:
|
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size Triton Torch
|
||||
0 4096.0 9.600000 9.600000
|
||||
1 8192.0 19.200000 15.999999
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1 8192.0 19.200000 19.200000
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2 16384.0 38.400001 38.400001
|
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3 32768.0 76.800002 76.800002
|
||||
3 32768.0 63.999998 63.999998
|
||||
4 65536.0 127.999995 127.999995
|
||||
5 131072.0 219.428568 219.428568
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||||
6 262144.0 341.333321 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 702.171410
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||||
10 4194304.0 780.190482 780.190482
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||||
11 8388608.0 812.429770 812.429770
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||||
12 16777216.0 833.084721 833.084721
|
||||
13 33554432.0 842.004273 843.811163
|
||||
13 33554432.0 842.004273 842.004273
|
||||
14 67108864.0 847.448255 848.362445
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||||
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 28.027 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 43.206 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>
|
||||
|
||||
@@ -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 512.000001 192.752942
|
||||
1 384.0 585.142862 585.142862 153.600004
|
||||
2 512.0 655.360017 585.142849 154.566038
|
||||
3 640.0 682.666684 640.000002 160.000000
|
||||
0 256.0 512.000001 546.133347 186.181817
|
||||
1 384.0 585.142862 585.142862 151.703707
|
||||
2 512.0 655.360017 606.814814 154.566038
|
||||
3 640.0 682.666684 640.000002 158.759699
|
||||
4 768.0 722.823517 664.216187 162.754967
|
||||
.. ... ... ... ...
|
||||
93 12160.0 814.058574 406.179533 198.429370
|
||||
94 12288.0 814.111783 415.661740 198.694297
|
||||
95 12416.0 812.498981 411.722274 198.259492
|
||||
96 12544.0 812.566838 412.971190 198.618504
|
||||
97 12672.0 812.633240 411.679167 198.679085
|
||||
93 12160.0 812.359066 405.755985 198.631953
|
||||
94 12288.0 814.111783 415.222812 198.794749
|
||||
95 12416.0 812.498981 412.149375 198.457532
|
||||
96 12544.0 812.566838 412.546756 198.667643
|
||||
97 12672.0 812.633240 411.679167 198.776477
|
||||
|
||||
[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 19.106 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.188 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>
|
||||
|
||||
@@ -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 ... 2.978909 2.978909
|
||||
1 384.0 7.372800 ... 8.507077 8.507077
|
||||
2 512.0 14.563555 ... 15.420235 15.420235
|
||||
1 384.0 7.372800 ... 8.507077 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 ... 34.028308 34.028308
|
||||
5 896.0 39.025776 ... 40.140799 39.025776
|
||||
5 896.0 37.971025 ... 39.025776 39.025776
|
||||
6 1024.0 49.932191 ... 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 65.684049
|
||||
9 1408.0 64.138541 ... 67.305878 66.485074
|
||||
10 1536.0 80.430545 ... 79.526831 78.643199
|
||||
11 1664.0 63.372618 ... 62.492442 62.061463
|
||||
11 1664.0 62.929456 ... 62.492442 62.061463
|
||||
12 1792.0 72.983276 ... 72.512412 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 ... 86.367588 85.632545
|
||||
16 2304.0 68.251065 ... 77.057651 76.563695
|
||||
17 2432.0 71.125224 ... 85.134737 84.367759
|
||||
18 2560.0 77.833728 ... 81.310171 80.908642
|
||||
19 2688.0 83.552988 ... 90.102270 89.464755
|
||||
20 2816.0 83.392363 ... 83.392363 82.916747
|
||||
21 2944.0 82.102191 ... 82.646820 82.102191
|
||||
22 3072.0 82.301023 ... 88.612060 88.473602
|
||||
23 3200.0 84.880639 ... 95.665176 95.096582
|
||||
24 3328.0 84.101981 ... 84.496824 84.496824
|
||||
25 3456.0 81.890873 ... 88.790274 90.892410
|
||||
26 3584.0 87.211821 ... 90.549237 97.628001
|
||||
27 3712.0 85.748791 ... 93.014284 87.475786
|
||||
28 3840.0 83.591840 ... 92.083268 88.261772
|
||||
29 3968.0 93.648452 ... 90.154371 86.788006
|
||||
30 4096.0 92.627833 ... 87.438257 82.340585
|
||||
13 1920.0 68.776119 ... 70.172588 70.172588
|
||||
14 2048.0 73.584279 ... 76.959706 76.608294
|
||||
15 2176.0 83.155572 ... 85.998493 85.269692
|
||||
16 2304.0 68.446623 ... 77.057651 76.563695
|
||||
17 2432.0 71.125224 ... 85.134737 83.614477
|
||||
18 2560.0 77.833728 ... 81.108913 80.908642
|
||||
19 2688.0 83.737433 ... 89.570381 89.044730
|
||||
20 2816.0 81.067298 ... 82.602666 83.233226
|
||||
21 2944.0 81.298583 ... 82.646820 82.784108
|
||||
22 3072.0 82.420822 ... 88.473602 88.335577
|
||||
23 3200.0 84.768213 ... 95.380032 94.814812
|
||||
24 3328.0 83.516586 ... 83.130825 83.808259
|
||||
25 3456.0 81.932484 ... 89.281913 91.304157
|
||||
26 3584.0 87.381330 ... 94.647779 97.628001
|
||||
27 3712.0 85.675250 ... 89.714725 87.552452
|
||||
28 3840.0 85.863352 ... 87.355452 91.398346
|
||||
29 3968.0 86.051653 ... 91.816356 86.788006
|
||||
30 4096.0 94.386588 ... 92.372834 88.185107
|
||||
|
||||
[31 rows x 5 columns]
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 26.690 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 26.832 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>
|
||||
|
||||
@@ -371,7 +371,7 @@ to explore the <cite>triton/language/random</cite> folder!</p>
|
||||
<dd><p>Nitish Srivastava and Geoffrey Hinton and Alex Krizhevsky and Ilya Sutskever and Ruslan Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting”, JMLR 2014</p>
|
||||
</dd>
|
||||
</dl>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.372 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.011 seconds)</p>
|
||||
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-04-low-memory-dropout-py">
|
||||
<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
||||
<p><a class="reference download internal" download="" href="../../_downloads/c9aed78977a4c05741d675a38dde3d7d/04-low-memory-dropout.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">04-low-memory-dropout.py</span></code></a></p>
|
||||
|
||||
@@ -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 1024.0 307.200008 99.096776 307.200008
|
||||
1 1536.0 351.085717 133.083026 338.201833
|
||||
2 2048.0 423.724127 161.684218 334.367350
|
||||
3 2560.0 458.507457 182.857144 328.556154
|
||||
4 3072.0 511.999982 191.501303 320.556515
|
||||
5 3584.0 551.384634 208.271186 308.301075
|
||||
6 4096.0 568.231237 220.412561 298.796351
|
||||
7 4608.0 495.928261 231.849059 286.507772
|
||||
8 5120.0 522.893618 242.845844 283.787523
|
||||
9 5632.0 536.380957 243.107920 291.310338
|
||||
10 6144.0 542.117638 248.661056 286.322318
|
||||
11 6656.0 525.473708 256.000009 286.279570
|
||||
12 7168.0 505.976473 261.844750 288.160801
|
||||
13 7680.0 481.253256 260.338991 277.172933
|
||||
14 8192.0 460.440290 268.957600 286.600589
|
||||
15 8704.0 416.958106 267.815384 284.987724
|
||||
0 1024.0 311.088617 99.096776 307.200008
|
||||
1 1536.0 351.085717 133.565214 338.201833
|
||||
2 2048.0 420.102553 158.554837 321.254900
|
||||
3 2560.0 461.954908 181.775141 328.556154
|
||||
4 3072.0 515.580429 190.020625 319.168834
|
||||
5 3584.0 547.872604 207.267476 306.106777
|
||||
6 4096.0 564.965515 219.919464 293.444785
|
||||
7 4608.0 498.162157 232.336141 291.031570
|
||||
8 5120.0 527.381977 243.809526 286.433562
|
||||
9 5632.0 545.032265 244.426754 291.310338
|
||||
10 6144.0 550.208948 251.202731 286.879370
|
||||
11 6656.0 534.260858 255.590406 285.257135
|
||||
12 7168.0 513.528374 256.000002 279.726817
|
||||
13 7680.0 487.619051 266.358392 280.547947
|
||||
14 8192.0 463.698115 260.063494 279.272725
|
||||
15 8704.0 416.127506 267.130429 284.212242
|
||||
16 9216.0 428.651187 272.729961 289.507855
|
||||
17 9728.0 438.857162 280.278512 288.950501
|
||||
18 10240.0 446.836366 286.433562 290.153487
|
||||
19 10752.0 428.651173 246.464170 289.941565
|
||||
20 11264.0 429.104745 245.091565 285.767446
|
||||
21 11776.0 421.826879 249.447482 288.686414
|
||||
22 12288.0 420.102570 254.453844 294.911986
|
||||
23 12800.0 415.135142 253.256381 289.811310
|
||||
24 13312.0 412.242569 252.559690 290.179836
|
||||
25 13824.0 404.604870 257.390218 292.571423
|
||||
26 14336.0 397.761846 254.862216 286.242939
|
||||
27 14848.0 383.999990 257.108233 289.012175
|
||||
28 15360.0 374.253788 257.610071 287.326580
|
||||
29 15872.0 366.982663 262.708969 291.006885
|
||||
17 9728.0 438.857162 280.278512 288.593329
|
||||
18 10240.0 447.650282 286.767793 288.112552
|
||||
19 10752.0 431.518385 246.935876 289.941565
|
||||
20 11264.0 428.424741 246.207655 287.897767
|
||||
21 11776.0 421.826879 249.888595 289.277383
|
||||
22 12288.0 417.722367 254.453844 294.911986
|
||||
23 12800.0 414.574901 253.569949 287.371378
|
||||
24 13312.0 412.242569 252.959629 289.653667
|
||||
25 13824.0 405.098897 257.190689 292.313649
|
||||
26 14336.0 399.146178 255.809666 289.372589
|
||||
27 14848.0 383.586664 256.922861 287.844912
|
||||
28 15360.0 376.932517 258.513318 288.225185
|
||||
29 15872.0 369.832994 261.267482 290.341468
|
||||
</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">'.'</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 11.692 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 11.696 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>
|
||||
|
||||
@@ -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>12:25.887</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>12:44.933</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<table class="docutils align-default">
|
||||
<colgroup>
|
||||
<col style="width: 85%" />
|
||||
@@ -183,23 +183,23 @@
|
||||
</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>05:26.690</p></td>
|
||||
<td><p>05:26.832</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>03:19.106</p></td>
|
||||
<td><p>03:23.188</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>02:11.692</p></td>
|
||||
<td><p>02:11.696</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>01:28.027</p></td>
|
||||
<td><p>01:43.206</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>
|
||||
<td><p>00:00.372</p></td>
|
||||
<td><p>00:00.011</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
|
||||
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