[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-02-17 00:40:30 +00:00
parent c1c43fcf06
commit 0cd3b626c5
158 changed files with 258 additions and 258 deletions

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@@ -235,7 +235,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
0 4096.0 9.600000 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 63.999998 76.800002
4 65536.0 127.999995 127.999995
5 131072.0 219.428568 219.428568
6 262144.0 341.333321 384.000001
@@ -255,7 +255,7 @@ 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:** ( 1 minutes 43.089 seconds)
**Total running time of the script:** ( 1 minutes 33.654 seconds)
.. _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
softmax-performance:
N Triton Torch (native) Torch (jit)
0 256.0 512.000001 546.133347 190.511628
0 256.0 512.000001 546.133347 188.321838
1 384.0 614.400016 585.142862 153.600004
2 512.0 655.360017 606.814814 154.566038
3 640.0 706.206879 640.000002 160.000000
4 768.0 722.823517 664.216187 162.754967
.. ... ... ... ...
93 12160.0 814.058574 406.179533 198.631953
94 12288.0 814.111783 415.661740 198.895304
95 12416.0 814.163950 412.577363 198.457532
96 12544.0 814.214963 412.971190 198.716830
97 12672.0 814.265046 412.097543 198.776477
93 12160.0 814.058574 406.179533 199.038365
94 12288.0 814.111783 415.222812 199.298541
95 12416.0 814.163950 412.149375 198.854847
96 12544.0 814.214963 412.971190 199.111113
97 12672.0 814.265046 411.679167 199.167004
[98 rows x 4 columns]
@@ -306,7 +306,7 @@ In the above plot, we can see that:
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 3 minutes 21.816 seconds)
**Total running time of the script:** ( 3 minutes 20.157 seconds)
.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:

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@@ -458,37 +458,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
matmul-performance:
M cuBLAS ... Triton Triton (+ LeakyReLU)
0 256.0 2.978909 ... 2.978909 2.978909
0 256.0 2.730667 ... 2.978909 2.978909
1 384.0 7.372800 ... 8.507077 7.899428
2 512.0 14.563555 ... 16.384000 16.384000
3 640.0 22.260869 ... 24.380953 24.380953
4 768.0 32.768000 ... 34.028308 34.028308
5 896.0 39.025776 ... 39.025776 39.025776
6 1024.0 51.150050 ... 52.428801 52.428801
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 49.932191 ... 52.428801 52.428801
7 1152.0 45.242181 ... 46.656000 46.656000
8 1280.0 51.200001 ... 56.888887 56.888887
9 1408.0 64.138541 ... 67.305878 66.485074
10 1536.0 80.430545 ... 79.526831 78.643199
11 1664.0 62.929456 ... 62.492442 62.061463
12 1792.0 72.983276 ... 71.588687 72.047592
13 1920.0 69.120002 ... 70.172588 70.172588
14 2048.0 73.262953 ... 76.608294 76.608294
15 2176.0 83.155572 ... 85.998493 85.632545
10 1536.0 79.526831 ... 79.526831 78.643199
11 1664.0 62.929456 ... 62.061463 61.636381
12 1792.0 72.512412 ... 72.047592 72.047592
13 1920.0 68.776119 ... 70.530615 70.530615
14 2048.0 73.584279 ... 76.959706 76.608294
15 2176.0 83.500614 ... 85.998493 85.632545
16 2304.0 68.446623 ... 76.319081 76.319081
17 2432.0 71.305746 ... 84.621881 84.115159
18 2560.0 78.019048 ... 81.108913 80.709358
19 2688.0 83.004501 ... 89.464755 89.464755
20 2816.0 82.916747 ... 82.759409 82.290955
21 2944.0 81.298583 ... 82.509987 82.646820
22 3072.0 81.825298 ... 84.135370 89.030036
23 3200.0 84.488448 ... 94.955488 94.604578
24 3328.0 82.939284 ... 81.346098 83.905938
25 3456.0 81.766291 ... 87.775250 90.790053
26 3584.0 87.296493 ... 97.947050 90.276496
27 3712.0 84.159518 ... 87.018592 85.748791
28 3840.0 84.874902 ... 92.313853 84.552479
29 3968.0 92.302520 ... 85.152783 91.028675
30 4096.0 86.703957 ... 85.434583 91.211502
17 2432.0 71.305746 ... 74.719317 85.134737
18 2560.0 78.019048 ... 80.709358 80.313727
19 2688.0 83.737433 ... 88.628636 89.254248
20 2816.0 79.879498 ... 83.233226 83.233226
21 2944.0 82.169877 ... 82.237674 82.102191
22 3072.0 81.121923 ... 88.612060 88.335577
23 3200.0 83.879425 ... 95.096582 95.380032
24 3328.0 82.843841 ... 84.200347 84.397770
25 3456.0 77.745004 ... 91.200871 84.686523
26 3584.0 86.540320 ... 97.840469 98.053863
27 3712.0 82.491612 ... 87.094458 86.867254
28 3840.0 81.859361 ... 90.058629 88.121115
29 3968.0 88.938731 ... 91.062642 86.880696
30 4096.0 93.012976 ... 91.242506 87.267706
[31 rows x 5 columns]
@@ -498,7 +498,7 @@ 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:** ( 6 minutes 1.969 seconds)
**Total running time of the script:** ( 5 minutes 57.748 seconds)
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:

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@@ -240,7 +240,7 @@ References
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 0.479 seconds)
**Total running time of the script:** ( 0 minutes 0.522 seconds)
.. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:

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@@ -38,36 +38,36 @@ Layer Normalization
layer-norm-backward:
N Triton Torch Apex
0 1024.0 311.088617 98.303995 307.200008
0 1024.0 307.200008 98.303995 307.200008
1 1536.0 347.773587 134.050910 341.333333
2 2048.0 420.102553 161.154101 334.367350
3 2560.0 458.507457 181.238943 330.322572
3 2560.0 455.111129 181.238943 330.322572
4 3072.0 511.999982 191.999993 320.556515
5 3584.0 551.384634 207.768111 310.527060
6 4096.0 564.965515 220.412561 297.890900
6 4096.0 568.231237 220.412561 298.796351
7 4608.0 504.986315 232.825259 286.507772
8 5120.0 529.655159 242.845844 285.104413
8 5120.0 527.381977 242.845844 284.444444
9 5632.0 542.843364 243.545956 289.438969
10 6144.0 546.133354 248.661056 286.879370
11 6656.0 532.479975 256.000009 285.767438
12 7168.0 507.469040 260.654538 286.242939
13 7680.0 479.999983 262.190612 278.850215
14 8192.0 463.698115 267.130429 284.939124
14 8192.0 462.607053 267.130429 284.939124
15 8704.0 417.791980 267.815384 284.987724
16 9216.0 431.157889 272.394084 288.751954
16 9216.0 430.319054 272.394084 288.751954
17 9728.0 438.857162 280.278512 290.027323
18 10240.0 449.287041 286.767793 290.153487
18 10240.0 449.287041 286.433562 290.153487
19 10752.0 426.525614 247.172406 290.594591
20 11264.0 427.071098 245.536784 286.676558
21 11776.0 423.089806 249.778170 288.981596
22 12288.0 419.504980 254.673582 294.176573
23 12800.0 414.016170 253.465340 289.538159
24 13312.0 411.181478 252.759501 289.916513
25 13824.0 404.112047 257.190689 292.056329
20 11264.0 426.397479 245.536784 286.676558
21 11776.0 422.457417 249.667843 288.686414
22 12288.0 419.504980 254.673582 294.029924
23 12800.0 413.458944 253.465340 289.538159
24 13312.0 411.181478 252.559690 289.916513
25 13824.0 404.112047 256.991469 292.313649
26 14336.0 393.215988 254.485198 286.719986
27 14848.0 384.829370 257.665934 289.012175
28 15360.0 373.495460 257.970599 287.326580
29 15872.0 371.274849 261.806182 289.679087
27 14848.0 385.245405 257.665934 289.246765
28 15360.0 373.874218 257.970599 287.326580
29 15872.0 371.274849 261.806182 289.899545
@@ -339,7 +339,7 @@ Layer Normalization
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 2 minutes 12.779 seconds)
**Total running time of the script:** ( 2 minutes 11.405 seconds)
.. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:

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@@ -5,16 +5,16 @@
Computation times
=================
**13:20.131** total execution time for **getting-started_tutorials** files:
**13:03.486** total execution time for **getting-started_tutorials** files:
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:01.969 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:57.748 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:21.816 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:20.157 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 02:12.779 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 02:11.405 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:43.089 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:33.654 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.479 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.522 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+