[GH-PAGES] Updated website
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@@ -239,7 +239,7 @@ 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 11.032 seconds)
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**Total running time of the script:** ( 0 minutes 10.984 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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@@ -49,7 +49,7 @@ Let us consider instead the case of a simple (numerically stabilized) softmax op
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# read 2MN elements ; write MN elements
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z = x - x_max[:, None]
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# read MN elements ; write MN elements
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numerator = torch.exp(x)
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numerator = torch.exp(z)
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# read MN elements ; write M elements
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denominator = numerator.sum(dim=1)
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# read 2MN elements ; write MN elements
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@@ -261,17 +261,17 @@ 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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0 256.0 512.000001 546.133347 273.066674
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1 384.0 585.142862 585.142862 267.130429
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2 512.0 630.153853 606.814814 264.258068
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3 640.0 682.666684 640.000002 269.473696
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4 768.0 702.171410 664.216187 273.066663
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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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2 512.0 630.153853 606.814814 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 162.754967
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.. ... ... ... ...
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93 12160.0 812.359066 406.179533 329.483481
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94 12288.0 812.429770 415.661740 329.602681
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95 12416.0 810.840807 412.149375 329.173158
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96 12544.0 810.925276 412.546756 329.292871
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97 12672.0 811.007961 412.097543 329.410251
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93 12160.0 812.359066 406.179533 198.936606
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94 12288.0 812.429770 416.101597 199.298541
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95 12416.0 810.840807 412.149375 198.854847
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96 12544.0 810.925276 412.971190 199.111113
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97 12672.0 811.007961 412.097543 199.167004
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[98 rows x 4 columns]
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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 8.174 seconds)
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**Total running time of the script:** ( 1 minutes 13.269 seconds)
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
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@@ -371,37 +371,37 @@ 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 2.978909 ... 2.978909 2.978909
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2 384.0 7.372800 ... 7.899428 7.899428
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1 256.0 2.730667 ... 2.978909 2.978909
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2 384.0 7.372800 ... 8.507077 8.507077
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3 512.0 14.563555 ... 16.384000 15.420235
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4 640.0 22.260869 ... 24.380953 24.380953
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5 768.0 32.768000 ... 34.028308 34.028308
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6 896.0 39.025776 ... 39.025776 39.025776
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7 1024.0 51.150050 ... 52.428801 52.428801
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7 1024.0 49.932191 ... 52.428801 52.428801
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8 1152.0 44.566925 ... 46.656000 46.656000
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9 1280.0 51.200001 ... 56.109587 56.109587
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10 1408.0 64.138541 ... 65.684049 65.684049
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11 1536.0 80.430545 ... 76.106321 75.296679
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12 1664.0 63.372618 ... 62.061463 61.636381
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13 1792.0 72.983276 ... 68.953520 68.533074
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14 1920.0 69.120002 ... 68.435645 68.435645
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15 2048.0 73.908442 ... 75.573044 75.234154
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16 2176.0 83.500614 ... 80.173899 79.855747
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17 2304.0 68.446623 ... 73.051599 72.607513
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18 2432.0 71.125224 ... 81.197876 80.963875
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19 2560.0 77.649287 ... 76.027843 76.740048
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20 2688.0 83.552988 ... 83.186525 82.823267
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21 2816.0 84.035084 ... 76.921000 79.733474
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22 2944.0 82.102191 ... 80.122235 78.729910
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23 3072.0 82.540970 ... 82.661468 82.661468
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24 3200.0 84.432717 ... 89.385477 84.432717
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25 3328.0 83.905938 ... 86.113988 86.528001
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26 3456.0 82.015834 ... 83.545665 84.156124
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27 3584.0 87.466332 ... 92.600816 84.988707
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28 3712.0 85.163978 ... 82.902362 83.666116
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29 3840.0 84.292684 ... 84.550462 85.070769
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30 3968.0 89.921841 ... 87.472354 87.409694
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31 4096.0 93.792965 ... 89.478485 90.260743
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10 1408.0 64.138541 ... 65.684049 64.902096
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11 1536.0 80.430545 ... 76.106321 76.106321
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12 1664.0 63.372618 ... 61.636381 61.636381
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13 1792.0 72.983276 ... 69.379162 68.953520
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14 1920.0 68.435645 ... 69.818184 68.776119
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15 2048.0 73.584279 ... 75.915006 75.234154
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16 2176.0 83.500614 ... 78.608000 79.540109
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17 2304.0 68.251065 ... 73.051599 72.607513
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18 2432.0 71.125224 ... 81.669953 80.269900
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19 2560.0 77.833728 ... 75.328737 74.812787
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20 2688.0 81.576466 ... 81.227100 82.823267
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21 2816.0 83.392363 ... 78.868366 77.330158
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22 2944.0 81.698415 ... 80.122235 79.356738
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23 3072.0 80.890151 ... 81.589488 83.391907
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24 3200.0 84.656085 ... 85.447263 88.033012
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25 3328.0 82.939284 ... 86.632127 82.558825
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26 3456.0 81.518272 ... 84.954233 84.420490
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27 3584.0 83.254996 ... 94.747514 95.654673
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28 3712.0 86.192706 ... 88.955779 88.797643
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29 3840.0 84.809814 ... 84.874902 84.356981
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30 3968.0 89.593789 ... 84.738843 84.212518
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31 4096.0 93.596744 ... 83.833686 90.933423
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[32 rows x 5 columns]
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@@ -411,7 +411,7 @@ 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:** ( 2 minutes 2.376 seconds)
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**Total running time of the script:** ( 2 minutes 16.432 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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@@ -5,12 +5,12 @@
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Computation times
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=================
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**03:21.583** total execution time for **getting-started_tutorials** files:
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**03:40.685** total execution time for **getting-started_tutorials** files:
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:02.376 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:16.432 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:08.174 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:13.269 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.032 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:10.984 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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