[GH-PAGES] Updated website
This commit is contained in:
@@ -255,7 +255,7 @@ 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 41.917 seconds)
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**Total running time of the script:** ( 1 minutes 47.895 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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@@ -278,17 +278,17 @@ 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 190.511628
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0 256.0 512.000001 546.133347 186.181817
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.. ... ... ... ...
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97 12672.0 811.007961 412.516771 199.167004
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93 12160.0 812.359066 406.179533 198.834951
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94 12288.0 812.429770 415.661740 199.197579
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96 12544.0 810.925276 412.971190 198.913776
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97 12672.0 811.007961 411.679167 198.971549
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[98 rows x 4 columns]
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@@ -306,7 +306,7 @@ 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 30.054 seconds)
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**Total running time of the script:** ( 3 minutes 31.309 seconds)
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
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@@ -459,37 +459,37 @@ 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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12 1792.0 72.983276 ... 73.460287 59.467852
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14 2048.0 73.908442 ... 78.398206 77.314362
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15 2176.0 83.155572 ... 87.876193 85.998493
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24 3328.0 83.226931 ... 85.398926 84.895397
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25 3456.0 81.766291 ... 91.511426 86.503829
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26 3584.0 83.876297 ... 95.756542 95.350361
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27 3712.0 84.159518 ... 88.837126 87.937800
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28 3840.0 85.070769 ... 93.326587 85.663823
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29 3968.0 91.198760 ... 87.097744 91.609561
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30 4096.0 86.204508 ... 93.792965 89.240508
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10 1536.0 80.430545 ... 81.355034 79.526831
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11 1664.0 63.372618 ... 63.372618 62.492442
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12 1792.0 72.983276 ... 73.943582 59.467852
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13 1920.0 69.467336 ... 71.257735 71.257735
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14 2048.0 73.584279 ... 78.398206 77.314362
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15 2176.0 83.500614 ... 87.876193 86.367588
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16 2304.0 68.251065 ... 78.064941 77.307030
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17 2432.0 71.305746 ... 86.444504 84.621881
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18 2560.0 78.019048 ... 82.331658 81.108913
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19 2688.0 83.369354 ... 90.966561 89.464755
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20 2816.0 79.587973 ... 84.197315 83.074685
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21 2944.0 81.967162 ... 83.060049 82.784108
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22 3072.0 82.420822 ... 87.924073 85.019675
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23 3200.0 84.768213 ... 96.458178 95.238096
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24 3328.0 83.905938 ... 85.096096 84.298943
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25 3456.0 82.604067 ... 91.304157 87.442050
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26 3584.0 87.211821 ... 98.375705 91.656871
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27 3712.0 84.874549 ... 89.035062 86.044224
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28 3840.0 84.744825 ... 93.484358 84.484863
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29 3968.0 92.582651 ... 84.976733 91.472214
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30 4096.0 86.256445 ... 88.475759 90.230403
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[31 rows x 5 columns]
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@@ -499,7 +499,7 @@ 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:** ( 6 minutes 38.507 seconds)
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**Total running time of the script:** ( 6 minutes 18.355 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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@@ -40,34 +40,34 @@ Layer Normalization
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N Triton Torch Apex
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0 1024.0 585.142849 277.694907 468.114273
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1 1536.0 630.153868 323.368435 511.999982
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2 2048.0 682.666643 337.814445 520.126988
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2 2048.0 668.734716 334.367358 520.126988
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3 2560.0 694.237267 362.477870 512.000013
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4 3072.0 712.347810 378.092307 501.551037
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5 3584.0 725.873439 384.859062 451.527536
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25 13824.0 481.882350 412.656711 379.389355
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26 14336.0 471.967074 405.975225 372.969090
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27 14848.0 461.297068 406.794504 375.304904
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29 15872.0 447.098578 406.974373 376.225175
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@@ -393,7 +393,7 @@ Layer Normalization
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 37.218 seconds)
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**Total running time of the script:** ( 5 minutes 33.735 seconds)
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.. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:
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@@ -390,7 +390,7 @@ This is a Triton implementation of the Flash Attention algorithm
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 0.073 seconds)
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**Total running time of the script:** ( 0 minutes 0.075 seconds)
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.. _sphx_glr_download_getting-started_tutorials_06-fused-attention.py:
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@@ -152,7 +152,7 @@ We can also customize the libdevice library path by passing the path to the `lib
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 0.010 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_07-libdevice-function.py:
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@@ -5,20 +5,20 @@
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Computation times
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=================
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**17:27.791** total execution time for **getting-started_tutorials** files:
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**17:11.392** 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``) | 06:38.507 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:18.355 | 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``) | 05:37.218 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 05:33.735 | 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``) | 03:30.054 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:31.309 | 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``) | 01:41.917 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:47.895 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``) | 00:00.073 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``) | 00:00.075 | 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``) | 00:00.012 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_07-libdevice-function.py` (``07-libdevice-function.py``) | 00:00.010 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_07-libdevice-function.py` (``07-libdevice-function.py``) | 00:00.011 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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