[GH-PAGES] Updated website
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@@ -219,10 +219,10 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
|
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0 4096.0 9.540372 9.600000
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|
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3 32768.0 76.800002 76.800002
|
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4 65536.0 127.999995 127.999995
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|
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6 262144.0 341.333321 384.000001
|
||||
6 262144.0 384.000001 384.000001
|
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8 1048576.0 614.400016 614.400016
|
||||
9 2097152.0 722.823517 722.823517
|
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@@ -230,7 +230,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
|
||||
11 8388608.0 812.429770 812.429770
|
||||
12 16777216.0 833.084721 833.084721
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14 67108864.0 848.362445 848.362445
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14 67108864.0 849.278610 848.362445
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15 134217728.0 851.577704 850.656574
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|
||||
@@ -239,7 +239,7 @@ 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 10.987 seconds)
|
||||
**Total running time of the script:** ( 0 minutes 11.018 seconds)
|
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|
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|
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
|
||||
|
@@ -262,16 +262,16 @@ 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 546.133347 273.066674
|
||||
1 384.0 585.142862 585.142862 261.446801
|
||||
2 512.0 655.360017 585.142849 264.258068
|
||||
1 384.0 585.142862 585.142862 267.130429
|
||||
2 512.0 630.153853 606.814814 264.258068
|
||||
3 640.0 682.666684 640.000002 269.473696
|
||||
4 768.0 702.171410 664.216187 273.066663
|
||||
.. ... ... ... ...
|
||||
93 12160.0 812.359066 406.179533 329.204728
|
||||
94 12288.0 812.429770 415.222812 329.602681
|
||||
95 12416.0 810.840807 412.149375 328.900662
|
||||
96 12544.0 810.925276 412.546756 329.292871
|
||||
97 12672.0 811.007961 412.097543 329.142870
|
||||
93 12160.0 812.359066 405.755985 329.483481
|
||||
94 12288.0 812.429770 415.661740 329.602681
|
||||
95 12416.0 810.840807 412.149375 329.173158
|
||||
96 12544.0 810.925276 412.971190 329.292871
|
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97 12672.0 811.007961 412.097543 329.410251
|
||||
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||||
[98 rows x 4 columns]
|
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|
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@@ -290,7 +290,7 @@ 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 8.170 seconds)
|
||||
**Total running time of the script:** ( 1 minutes 8.191 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
|
||||
|
@@ -371,37 +371,37 @@ 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
|
||||
1 256.0 2.730667 ... 3.276800 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 ... 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 37.971025 ... 39.025776 37.971025
|
||||
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|
||||
7 1024.0 49.932191 ... 52.428801 52.428801
|
||||
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|
||||
8 1152.0 44.566925 ... 45.938215 45.938215
|
||||
9 1280.0 51.200001 ... 56.109587 56.109587
|
||||
10 1408.0 64.138541 ... 65.684049 65.684049
|
||||
11 1536.0 80.430545 ... 76.106321 76.106321
|
||||
12 1664.0 63.372618 ... 61.636381 61.636381
|
||||
13 1792.0 72.983276 ... 68.533074 68.533074
|
||||
14 1920.0 68.098521 ... 70.172588 70.172588
|
||||
15 2048.0 73.908442 ... 75.234154 75.573044
|
||||
16 2176.0 83.155572 ... 80.173899 79.855747
|
||||
17 2304.0 68.251065 ... 73.051599 72.828879
|
||||
18 2432.0 71.125224 ... 81.433227 81.433227
|
||||
19 2560.0 77.833728 ... 76.920185 75.676673
|
||||
20 2688.0 83.552988 ... 80.880718 82.823267
|
||||
21 2816.0 82.446516 ... 78.868366 79.733474
|
||||
22 2944.0 82.373605 ... 80.251257 79.610276
|
||||
23 3072.0 77.993256 ... 81.943708 83.514905
|
||||
24 3200.0 84.210524 ... 89.887639 84.544253
|
||||
25 3328.0 83.130825 ... 81.346098 82.088138
|
||||
26 3456.0 80.140726 ... 82.943999 81.600781
|
||||
27 3584.0 87.296493 ... 95.451583 96.269155
|
||||
28 3712.0 84.301560 ... 89.194055 89.035062
|
||||
29 3840.0 85.267542 ... 83.718392 84.292684
|
||||
30 3968.0 89.921841 ... 87.035620 86.664727
|
||||
31 4096.0 92.820009 ... 91.366730 91.741443
|
||||
10 1408.0 64.138541 ... 65.684049 58.621246
|
||||
11 1536.0 79.526831 ... 76.106321 75.296679
|
||||
12 1664.0 63.372618 ... 62.061463 61.636381
|
||||
13 1792.0 72.983276 ... 69.379162 68.953520
|
||||
14 1920.0 66.782607 ... 70.172588 70.172588
|
||||
15 2048.0 73.908442 ... 75.573044 75.234154
|
||||
16 2176.0 83.155572 ... 80.817862 79.226957
|
||||
17 2304.0 68.251065 ... 73.051599 72.607513
|
||||
18 2432.0 71.125224 ... 80.041209 80.963875
|
||||
19 2560.0 77.101175 ... 77.101175 76.027843
|
||||
20 2688.0 83.922689 ... 80.880718 83.369354
|
||||
21 2816.0 78.584162 ... 78.726003 79.011245
|
||||
22 2944.0 82.373605 ... 78.481940 80.640830
|
||||
23 3072.0 79.415291 ... 84.892208 83.761985
|
||||
24 3200.0 80.604535 ... 89.761569 87.312416
|
||||
25 3328.0 83.130825 ... 82.369902 81.715431
|
||||
26 3456.0 81.108217 ... 87.347312 83.200794
|
||||
27 3584.0 86.707226 ... 96.579370 88.499397
|
||||
28 3712.0 80.627396 ... 83.736248 81.950243
|
||||
29 3840.0 80.197243 ... 85.930069 86.602979
|
||||
30 3968.0 91.472214 ... 87.472354 87.409694
|
||||
31 4096.0 92.948562 ... 91.553703 91.678778
|
||||
|
||||
[32 rows x 5 columns]
|
||||
|
||||
@@ -411,7 +411,7 @@ 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 5.849 seconds)
|
||||
**Total running time of the script:** ( 2 minutes 12.196 seconds)
|
||||
|
||||
|
||||
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
|
||||
|
@@ -5,12 +5,12 @@
|
||||
|
||||
Computation times
|
||||
=================
|
||||
**03:25.006** total execution time for **getting-started_tutorials** files:
|
||||
**03:31.405** total execution time for **getting-started_tutorials** files:
|
||||
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:05.849 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:12.196 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:08.170 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:08.191 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:10.987 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.018 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
|
@@ -308,10 +308,10 @@ for different problem sizes.</p>
|
||||
0 4096.0 9.540372 9.600000
|
||||
1 8192.0 19.200000 19.200000
|
||||
2 16384.0 38.400001 38.400001
|
||||
3 32768.0 63.999998 63.999998
|
||||
3 32768.0 76.800002 76.800002
|
||||
4 65536.0 127.999995 127.999995
|
||||
5 131072.0 219.428568 219.428568
|
||||
6 262144.0 341.333321 384.000001
|
||||
6 262144.0 384.000001 384.000001
|
||||
7 524288.0 472.615390 472.615390
|
||||
8 1048576.0 614.400016 614.400016
|
||||
9 2097152.0 722.823517 722.823517
|
||||
@@ -319,11 +319,11 @@ for different problem sizes.</p>
|
||||
11 8388608.0 812.429770 812.429770
|
||||
12 16777216.0 833.084721 833.084721
|
||||
13 33554432.0 843.811163 843.811163
|
||||
14 67108864.0 848.362445 848.362445
|
||||
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 10.987 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 11.018 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>
|
||||
|
@@ -347,16 +347,16 @@ We will then compare its performance against (1) <code class="code docutils lite
|
||||
<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 546.133347 273.066674
|
||||
1 384.0 585.142862 585.142862 261.446801
|
||||
2 512.0 655.360017 585.142849 264.258068
|
||||
1 384.0 585.142862 585.142862 267.130429
|
||||
2 512.0 630.153853 606.814814 264.258068
|
||||
3 640.0 682.666684 640.000002 269.473696
|
||||
4 768.0 702.171410 664.216187 273.066663
|
||||
.. ... ... ... ...
|
||||
93 12160.0 812.359066 406.179533 329.204728
|
||||
94 12288.0 812.429770 415.222812 329.602681
|
||||
95 12416.0 810.840807 412.149375 328.900662
|
||||
96 12544.0 810.925276 412.546756 329.292871
|
||||
97 12672.0 811.007961 412.097543 329.142870
|
||||
93 12160.0 812.359066 405.755985 329.483481
|
||||
94 12288.0 812.429770 415.661740 329.602681
|
||||
95 12416.0 810.840807 412.149375 329.173158
|
||||
96 12544.0 810.925276 412.971190 329.292871
|
||||
97 12672.0 811.007961 412.097543 329.410251
|
||||
|
||||
[98 rows x 4 columns]
|
||||
</pre></div>
|
||||
@@ -370,7 +370,7 @@ 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 8.170 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 8.191 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>
|
||||
|
@@ -476,42 +476,42 @@ tensor(True, device='cuda:0')
|
||||
<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 ... 3.276800 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 ... 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 37.971025 ... 39.025776 37.971025
|
||||
6 896.0 39.025776 ... 39.025776 39.025776
|
||||
7 1024.0 49.932191 ... 52.428801 52.428801
|
||||
8 1152.0 44.566925 ... 46.656000 45.938215
|
||||
8 1152.0 44.566925 ... 45.938215 45.938215
|
||||
9 1280.0 51.200001 ... 56.109587 56.109587
|
||||
10 1408.0 64.138541 ... 65.684049 65.684049
|
||||
11 1536.0 80.430545 ... 76.106321 76.106321
|
||||
12 1664.0 63.372618 ... 61.636381 61.636381
|
||||
13 1792.0 72.983276 ... 68.533074 68.533074
|
||||
14 1920.0 68.098521 ... 70.172588 70.172588
|
||||
15 2048.0 73.908442 ... 75.234154 75.573044
|
||||
16 2176.0 83.155572 ... 80.173899 79.855747
|
||||
17 2304.0 68.251065 ... 73.051599 72.828879
|
||||
18 2432.0 71.125224 ... 81.433227 81.433227
|
||||
19 2560.0 77.833728 ... 76.920185 75.676673
|
||||
20 2688.0 83.552988 ... 80.880718 82.823267
|
||||
21 2816.0 82.446516 ... 78.868366 79.733474
|
||||
22 2944.0 82.373605 ... 80.251257 79.610276
|
||||
23 3072.0 77.993256 ... 81.943708 83.514905
|
||||
24 3200.0 84.210524 ... 89.887639 84.544253
|
||||
25 3328.0 83.130825 ... 81.346098 82.088138
|
||||
26 3456.0 80.140726 ... 82.943999 81.600781
|
||||
27 3584.0 87.296493 ... 95.451583 96.269155
|
||||
28 3712.0 84.301560 ... 89.194055 89.035062
|
||||
29 3840.0 85.267542 ... 83.718392 84.292684
|
||||
30 3968.0 89.921841 ... 87.035620 86.664727
|
||||
31 4096.0 92.820009 ... 91.366730 91.741443
|
||||
10 1408.0 64.138541 ... 65.684049 58.621246
|
||||
11 1536.0 79.526831 ... 76.106321 75.296679
|
||||
12 1664.0 63.372618 ... 62.061463 61.636381
|
||||
13 1792.0 72.983276 ... 69.379162 68.953520
|
||||
14 1920.0 66.782607 ... 70.172588 70.172588
|
||||
15 2048.0 73.908442 ... 75.573044 75.234154
|
||||
16 2176.0 83.155572 ... 80.817862 79.226957
|
||||
17 2304.0 68.251065 ... 73.051599 72.607513
|
||||
18 2432.0 71.125224 ... 80.041209 80.963875
|
||||
19 2560.0 77.101175 ... 77.101175 76.027843
|
||||
20 2688.0 83.922689 ... 80.880718 83.369354
|
||||
21 2816.0 78.584162 ... 78.726003 79.011245
|
||||
22 2944.0 82.373605 ... 78.481940 80.640830
|
||||
23 3072.0 79.415291 ... 84.892208 83.761985
|
||||
24 3200.0 80.604535 ... 89.761569 87.312416
|
||||
25 3328.0 83.130825 ... 82.369902 81.715431
|
||||
26 3456.0 81.108217 ... 87.347312 83.200794
|
||||
27 3584.0 86.707226 ... 96.579370 88.499397
|
||||
28 3712.0 80.627396 ... 83.736248 81.950243
|
||||
29 3840.0 80.197243 ... 85.930069 86.602979
|
||||
30 3968.0 91.472214 ... 87.472354 87.409694
|
||||
31 4096.0 92.948562 ... 91.553703 91.678778
|
||||
|
||||
[32 rows x 5 columns]
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 5.849 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.196 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">
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<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>
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<p><strong>03:25.006</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
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||||
<p><strong>03:31.405</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
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<table class="docutils align-default">
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<colgroup>
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<col style="width: 85%" />
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@@ -183,15 +183,15 @@
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</colgroup>
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<tbody>
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||||
<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>02:05.849</p></td>
|
||||
<td><p>02:12.196</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>01:08.170</p></td>
|
||||
<td><p>01:08.191</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>00:10.987</p></td>
|
||||
<td><p>00:11.018</p></td>
|
||||
<td><p>0.0 MB</p></td>
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||||
</tr>
|
||||
</tbody>
|
||||
|