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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 11.050 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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@@ -303,14 +303,14 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
|
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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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.. ... ... ... ...
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97 12672.0 811.007961 412.097543 199.264875
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97 12672.0 809.389265 412.097543 199.167004
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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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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 1 minutes 12.603 seconds)
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**Total running time of the script:** ( 1 minutes 12.602 seconds)
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
|
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@@ -471,37 +471,37 @@ 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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0 128.0 0.455111 ... 0.512000 0.512000
|
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1 256.0 2.730667 ... 2.978909 2.978909
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|
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|
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|
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17 2304.0 68.446623 ... 73.275679 73.275679
|
||||
18 2432.0 71.125224 ... 82.147552 81.197876
|
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19 2560.0 77.833728 ... 76.027843 75.328737
|
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20 2688.0 82.642823 ... 83.004501 83.737433
|
||||
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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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24 3200.0 84.210524 ... 89.260810 87.791493
|
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25 3328.0 83.130825 ... 86.736504 82.275764
|
||||
26 3456.0 78.578525 ... 83.459178 85.767626
|
||||
27 3584.0 87.808000 ... 92.410473 95.148565
|
||||
28 3712.0 85.601834 ... 85.601834 88.876645
|
||||
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|
||||
30 3968.0 92.512459 ... 83.807647 83.520835
|
||||
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|
||||
|
||||
[32 rows x 5 columns]
|
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|
||||
@@ -511,7 +511,7 @@ 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 14.775 seconds)
|
||||
**Total running time of the script:** ( 2 minutes 16.405 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
|
||||
|
@@ -5,12 +5,12 @@
|
||||
|
||||
Computation times
|
||||
=================
|
||||
**03:38.428** total execution time for **getting-started_tutorials** files:
|
||||
**03:39.988** total execution time for **getting-started_tutorials** files:
|
||||
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:14.775 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:16.405 | 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_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.602 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.050 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:10.981 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
|
@@ -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 11.050 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>
|
||||
|
@@ -388,14 +388,14 @@ We will then compare its performance against (1) <code class="code docutils lite
|
||||
0 256.0 512.000001 546.133347 186.181817
|
||||
1 384.0 585.142862 585.142862 153.600004
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||||
2 512.0 630.153853 585.142849 154.566038
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3 640.0 660.645170 640.000002 160.000000
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||||
3 640.0 682.666684 640.000002 160.000000
|
||||
4 768.0 702.171410 664.216187 163.839992
|
||||
.. ... ... ... ...
|
||||
93 12160.0 812.359066 405.755985 199.038365
|
||||
94 12288.0 812.429770 415.661740 199.298541
|
||||
95 12416.0 810.840807 412.149375 198.954424
|
||||
96 12544.0 810.925276 412.971190 199.209928
|
||||
97 12672.0 811.007961 412.097543 199.264875
|
||||
97 12672.0 809.389265 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 12.603 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 12.602 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>
|
||||
|
@@ -575,42 +575,42 @@ 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 2.730667 ... 2.978909 2.978909
|
||||
1 256.0 2.978909 ... 3.276800 2.978909
|
||||
2 384.0 7.372800 ... 8.507077 8.507077
|
||||
3 512.0 14.563555 ... 15.420235 15.420235
|
||||
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 ... 40.140799 39.025776
|
||||
7 1024.0 49.932191 ... 53.773130 52.428801
|
||||
8 1152.0 44.566925 ... 46.656000 46.656000
|
||||
8 1152.0 45.242181 ... 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 80.430545 ... 76.106321 76.106321
|
||||
12 1664.0 63.372618 ... 62.492442 62.061463
|
||||
12 1664.0 63.372618 ... 62.061463 62.061463
|
||||
13 1792.0 72.983276 ... 69.810085 69.810085
|
||||
14 1920.0 69.467336 ... 69.467336 68.098521
|
||||
15 2048.0 73.584279 ... 75.234154 68.200062
|
||||
16 2176.0 82.813365 ... 78.916269 79.855747
|
||||
17 2304.0 68.446623 ... 73.275679 73.275679
|
||||
18 2432.0 71.125224 ... 82.147552 81.197876
|
||||
19 2560.0 77.833728 ... 76.027843 75.328737
|
||||
20 2688.0 82.642823 ... 83.004501 83.737433
|
||||
21 2816.0 82.759409 ... 78.726003 79.443003
|
||||
22 2944.0 80.771529 ... 80.122235 77.505492
|
||||
23 3072.0 81.707223 ... 82.062468 83.146995
|
||||
24 3200.0 80.301128 ... 86.253369 88.888888
|
||||
25 3328.0 82.939284 ... 86.632127 81.994643
|
||||
26 3456.0 81.849303 ... 85.494768 84.686523
|
||||
27 3584.0 84.190443 ... 95.553020 95.654673
|
||||
28 3712.0 82.423549 ... 88.797643 84.230479
|
||||
29 3840.0 82.716526 ... 83.214447 81.317647
|
||||
30 3968.0 88.809270 ... 82.392935 83.807647
|
||||
31 4096.0 93.531519 ... 89.777746 89.359338
|
||||
14 1920.0 69.120002 ... 70.172588 69.120002
|
||||
15 2048.0 73.584279 ... 74.898285 73.584279
|
||||
16 2176.0 82.813365 ... 78.916269 79.540109
|
||||
17 2304.0 68.056616 ... 73.275679 73.275679
|
||||
18 2432.0 71.125224 ... 81.197876 81.908060
|
||||
19 2560.0 77.649287 ... 76.560748 75.676673
|
||||
20 2688.0 84.108772 ... 81.053536 84.108772
|
||||
21 2816.0 80.469019 ... 79.298560 78.726003
|
||||
22 2944.0 81.832567 ... 79.737653 79.104810
|
||||
23 3072.0 82.540970 ... 80.890151 83.146995
|
||||
24 3200.0 84.210524 ... 89.260810 87.791493
|
||||
25 3328.0 83.130825 ... 86.736504 82.275764
|
||||
26 3456.0 78.578525 ... 83.459178 85.767626
|
||||
27 3584.0 87.808000 ... 92.410473 95.148565
|
||||
28 3712.0 85.601834 ... 85.601834 88.876645
|
||||
29 3840.0 84.615146 ... 86.875096 87.148936
|
||||
30 3968.0 92.512459 ... 83.807647 83.520835
|
||||
31 4096.0 93.596744 ... 90.748973 90.321484
|
||||
|
||||
[32 rows x 5 columns]
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 14.775 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 16.405 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>03:38.428</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>03:39.988</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>02:14.775</p></td>
|
||||
<td><p>02:16.405</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>01:12.603</p></td>
|
||||
<td><p>01:12.602</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>00:11.050</p></td>
|
||||
<td><p>00:10.981</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
|