[GH-PAGES] Updated website
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@@ -237,10 +237,10 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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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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5 131072.0 219.428568 219.428568
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6 262144.0 341.333321 341.333321
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6 262144.0 341.333321 384.000001
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7 524288.0 472.615390 472.615390
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8 1048576.0 614.400016 614.400016
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9 2097152.0 722.823517 722.823517
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9 2097152.0 702.171410 722.823517
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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
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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 11.019 seconds)
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**Total running time of the script:** ( 0 minutes 11.001 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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@@ -302,15 +302,15 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
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N Triton Torch (native) Torch (jit)
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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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2 512.0 655.360017 585.142849 154.566038
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3 640.0 660.645170 640.000002 160.000000
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4 768.0 702.171410 664.216187 163.839992
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.. ... ... ... ...
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93 12160.0 812.359066 406.179533 198.733401
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94 12288.0 812.429770 416.101597 199.096718
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96 12544.0 810.925276 412.546756 198.913776
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97 12672.0 811.007961 412.097543 198.873965
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93 12160.0 812.359066 406.179533 199.038365
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94 12288.0 812.429770 415.661740 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 199.209928
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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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@@ -328,7 +328,7 @@ 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 12.589 seconds)
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**Total running time of the script:** ( 1 minutes 12.597 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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0 256.0 2.978909 ... 2.978909 2.978909
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1 384.0 7.372800 ... 8.507077 8.507077
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1 384.0 7.372800 ... 8.507077 7.899428
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2 512.0 14.563555 ... 16.384000 16.384000
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3 640.0 22.260869 ... 24.380953 24.380953
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4 768.0 32.768000 ... 34.028308 34.028308
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5 896.0 39.025776 ... 39.025776 35.994954
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5 896.0 39.025776 ... 39.025776 39.025776
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6 1024.0 49.932191 ... 52.428801 52.428801
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9 1408.0 64.138541 ... 63.392744 62.664092
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8 1280.0 51.200001 ... 56.109587 56.109587
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9 1408.0 64.138541 ... 62.664092 62.664092
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10 1536.0 80.430545 ... 75.296679 75.296679
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14 2048.0 73.908442 ... 74.898285 74.565406
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15 2176.0 83.500614 ... 81.143743 78.916269
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16 2304.0 68.056616 ... 73.501144 72.828879
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17 2432.0 71.125224 ... 82.388456 81.433227
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18 2560.0 77.833728 ... 77.283019 75.851852
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19 2688.0 81.752274 ... 83.369354 80.708630
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23 3200.0 81.528664 ... 90.140846 86.603520
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24 3328.0 83.034941 ... 87.262177 82.558825
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25 3456.0 79.273916 ... 80.460651 79.040756
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26 3584.0 87.466332 ... 93.080114 85.876512
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27 3712.0 85.091436 ... 82.698613 81.950243
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28 3840.0 81.019778 ... 86.063813 86.197974
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29 3968.0 93.219206 ... 87.850207 86.973584
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30 4096.0 93.727466 ... 84.894196 90.018600
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13 1920.0 69.120002 ... 67.434145 70.172588
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14 2048.0 73.908442 ... 74.565406 74.565406
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15 2176.0 83.155572 ... 80.494588 81.143743
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16 2304.0 68.251065 ... 73.501144 73.501144
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17 2432.0 71.305746 ... 71.852848 82.147552
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18 2560.0 77.649287 ... 76.560748 75.676673
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19 2688.0 83.922689 ... 79.524227 83.737433
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20 2816.0 80.617762 ... 79.011245 77.330158
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21 2944.0 81.832567 ... 77.626218 77.747321
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22 3072.0 82.540970 ... 83.638266 84.135370
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23 3200.0 84.321474 ... 89.260810 88.642656
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24 3328.0 82.369902 ... 84.596116 87.051143
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25 3456.0 79.508447 ... 83.980802 84.864807
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26 3584.0 84.905939 ... 86.707226 91.007486
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27 3712.0 85.822459 ... 79.853993 84.017953
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28 3840.0 84.874902 ... 87.355452 82.778440
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29 3968.0 88.167587 ... 80.278903 80.703662
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30 4096.0 93.596744 ... 89.181212 89.062862
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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:** ( 1 minutes 59.549 seconds)
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**Total running time of the script:** ( 1 minutes 57.433 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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@@ -5,14 +5,14 @@
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Computation times
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=================
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**03:23.342** total execution time for **getting-started_tutorials** files:
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**03:21.216** 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``) | 01:59.549 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 01:57.433 | 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``) | 01:12.589 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.597 | 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``) | 00:11.019 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.001 | 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``) | 00:00.185 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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