[GH-PAGES] Updated website

This commit is contained in:
Philippe Tillet
2022-08-10 00:48:34 +00:00
parent 24ae9b82dd
commit 4b51054036
165 changed files with 288 additions and 288 deletions

View File

@@ -1,4 +1,4 @@
# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 4a57db4e5b36e9c2997013e2fd53e962
config: 425a19caee966fd0c51df8134917a3e4
tags: 645f666f9bcd5a90fca523b33c5a78b7

Binary file not shown.

Binary file not shown.

Binary file not shown.

Before

Width:  |  Height:  |  Size: 24 KiB

After

Width:  |  Height:  |  Size: 24 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 15 KiB

After

Width:  |  Height:  |  Size: 16 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 36 KiB

After

Width:  |  Height:  |  Size: 36 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 23 KiB

After

Width:  |  Height:  |  Size: 23 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 59 KiB

After

Width:  |  Height:  |  Size: 60 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 34 KiB

After

Width:  |  Height:  |  Size: 34 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 36 KiB

After

Width:  |  Height:  |  Size: 36 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 22 KiB

After

Width:  |  Height:  |  Size: 22 KiB

View File

@@ -233,19 +233,19 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
vector-add-performance:
size Triton Torch
0 4096.0 9.600000 9.600000
1 8192.0 19.200000 15.999999
1 8192.0 19.200000 19.200000
2 16384.0 38.400001 38.400001
3 32768.0 76.800002 76.800002
4 65536.0 127.999995 127.999995
5 131072.0 219.428568 219.428568
6 262144.0 384.000001 384.000001
6 262144.0 341.333321 384.000001
7 524288.0 472.615390 472.615390
8 1048576.0 614.400016 614.400016
9 2097152.0 722.823517 722.823517
10 4194304.0 780.190482 780.190482
11 8388608.0 812.429770 812.429770
12 16777216.0 833.084721 833.084721
13 33554432.0 842.004273 842.004273
13 33554432.0 842.004273 843.811163
14 67108864.0 847.448255 848.362445
15 134217728.0 849.737435 850.656574
@@ -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 41.831 seconds)
**Total running time of the script:** ( 1 minutes 48.722 seconds)
.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:

View File

@@ -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)
0 256.0 546.133347 546.133347 190.511628
1 384.0 614.400016 585.142862 151.703707
2 512.0 655.360017 606.814814 156.038096
0 256.0 512.000001 546.133347 186.181817
1 384.0 614.400016 585.142862 153.600004
2 512.0 655.360017 585.142849 154.566038
3 640.0 706.206879 640.000002 160.000000
4 768.0 722.823517 664.216187 163.839992
.. ... ... ... ...
93 12160.0 812.359066 405.333344 199.038365
94 12288.0 812.429770 415.222812 199.197579
95 12416.0 812.498981 411.296057 198.805107
96 12544.0 811.745227 412.971190 199.012395
97 12672.0 811.007961 412.097543 199.167004
93 12160.0 812.359066 405.755985 198.936606
94 12288.0 812.429770 415.661740 199.197579
95 12416.0 812.498981 411.722274 198.755369
96 12544.0 810.925276 412.971190 199.012395
97 12672.0 811.007961 412.097543 199.069228
[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 28.967 seconds)
**Total running time of the script:** ( 3 minutes 32.036 seconds)
.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:

View File

@@ -459,37 +459,37 @@ 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 ... 3.276800 3.276800
0 256.0 2.730667 ... 2.978909 3.276800
1 384.0 7.372800 ... 8.507077 8.507077
2 512.0 14.563555 ... 16.384000 16.384000
2 512.0 14.563555 ... 16.384000 15.420235
3 640.0 22.260869 ... 24.380953 24.380953
4 768.0 32.768000 ... 35.389441 34.028308
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 49.932191 ... 53.773130 52.428801
5 896.0 37.971025 ... 40.140799 39.025776
6 1024.0 49.932191 ... 53.773130 53.092457
7 1152.0 45.242181 ... 48.161033 48.161033
8 1280.0 51.200001 ... 57.690139 57.690139
9 1408.0 64.138541 ... 69.009825 68.147202
9 1408.0 64.138541 ... 69.009825 67.305878
10 1536.0 80.430545 ... 81.355034 79.526831
11 1664.0 63.372618 ... 63.372618 62.492442
12 1792.0 72.983276 ... 73.460287 59.467852
11 1664.0 62.929456 ... 63.372618 62.492442
12 1792.0 72.512412 ... 73.460287 59.467852
13 1920.0 69.120002 ... 71.626943 71.257735
14 2048.0 73.908442 ... 78.398206 77.314362
15 2176.0 83.500614 ... 87.876193 86.367588
15 2176.0 83.500614 ... 87.876193 85.998493
16 2304.0 68.446623 ... 78.064941 77.057651
17 2432.0 71.305746 ... 85.915795 83.366361
18 2560.0 77.833728 ... 81.715711 81.310171
19 2688.0 83.369354 ... 90.532356 90.102270
20 2816.0 81.445766 ... 84.035084 83.873477
21 2944.0 81.564701 ... 83.477440 82.921853
22 3072.0 82.420822 ... 89.735509 88.750943
23 3200.0 84.544253 ... 97.116842 95.096582
24 3328.0 83.905938 ... 85.806075 83.808259
25 3456.0 82.773682 ... 90.180725 90.687926
26 3584.0 87.042978 ... 99.244365 98.268190
27 3712.0 81.482335 ... 88.718781 88.248537
28 3840.0 82.531346 ... 89.043476 89.912191
29 3968.0 86.911637 ... 92.652949 84.094627
30 4096.0 93.368854 ... 83.313299 89.928129
17 2432.0 71.305746 ... 85.393507 75.522751
18 2560.0 77.833728 ... 82.125311 80.908642
19 2688.0 83.922689 ... 90.966561 89.464755
20 2816.0 81.067298 ... 84.360174 83.873477
21 2944.0 81.967162 ... 83.337844 81.832567
22 3072.0 82.420822 ... 89.310890 88.473602
23 3200.0 83.879425 ... 95.238096 87.671229
24 3328.0 82.369902 ... 85.602017 81.994643
25 3456.0 80.864158 ... 84.332184 90.281712
26 3584.0 87.127323 ... 97.947050 97.205829
27 3712.0 84.159518 ... 89.035062 87.552452
28 3840.0 81.138664 ... 86.332554 90.279183
29 3968.0 87.913500 ... 91.954739 86.358055
30 4096.0 93.271527 ... 84.254693 82.418802
[31 rows x 5 columns]
@@ -499,7 +499,7 @@ 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 37.798 seconds)
**Total running time of the script:** ( 7 minutes 19.813 seconds)
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:

View File

@@ -240,7 +240,7 @@ References
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 0.012 seconds)
**Total running time of the script:** ( 0 minutes 0.281 seconds)
.. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:

View File

@@ -38,34 +38,34 @@ Layer Normalization
layer-norm:
N Triton Torch Apex
0 1024.0 585.142849 277.694907 468.114273
0 1024.0 606.814814 277.694907 468.114273
1 1536.0 630.153868 323.368435 511.999982
2 2048.0 668.734716 337.814445 520.126988
3 2560.0 694.237267 362.477870 518.481028
4 3072.0 712.347810 378.092307 501.551037
5 3584.0 725.873439 384.859062 458.751978
6 4096.0 728.177767 383.251446 455.111095
7 4608.0 670.254540 396.387087 423.724136
8 5120.0 688.403381 395.748783 417.959197
9 5632.0 704.000002 396.969169 413.357796
10 6144.0 702.171410 404.543206 409.600010
2 2048.0 682.666643 337.814445 520.126988
3 2560.0 694.237267 362.477870 512.000013
4 3072.0 712.347810 378.092307 506.721668
5 3584.0 725.873439 384.859062 455.111115
6 4096.0 728.177767 381.023256 451.972420
7 4608.0 670.254540 396.387087 431.157877
8 5120.0 688.403381 397.669909 422.268057
9 5632.0 704.000002 395.228063 415.262685
10 6144.0 702.171410 402.885254 409.600010
11 6656.0 700.631610 400.360920 400.360920
12 7168.0 690.891575 391.426634 387.459443
13 7680.0 678.895043 392.587863 385.203746
14 8192.0 636.271854 388.937680 368.179771
15 8704.0 627.315309 387.922008 380.502740
16 9216.0 606.814809 405.098894 382.010363
17 9728.0 587.350922 409.599987 382.427505
18 10240.0 566.920437 408.578556 382.803739
19 10752.0 547.872604 411.559798 380.601764
20 11264.0 533.207081 401.389743 372.363645
21 11776.0 520.486200 408.711507 377.587162
22 12288.0 516.031509 413.911572 383.251457
23 12800.0 504.433489 410.420828 377.163903
24 13312.0 494.180982 404.159395 375.647260
25 13824.0 482.934503 410.359948 378.739711
26 14336.0 472.940209 403.121247 374.185964
27 14848.0 461.297068 405.406157 374.712936
12 7168.0 690.891575 392.767108 382.293315
13 7680.0 678.895043 393.846167 386.415087
14 8192.0 633.198054 394.795186 376.643677
15 8704.0 624.502255 389.005597 379.465939
16 9216.0 606.814809 406.214877 382.010363
17 9728.0 587.350922 408.524944 383.369452
18 10240.0 564.965524 409.600010 382.803739
19 10752.0 546.133312 411.559798 380.601764
20 11264.0 532.419472 404.089694 371.595879
21 11776.0 520.486200 409.599991 377.587162
22 12288.0 513.336807 413.911572 383.251457
23 12800.0 504.433489 409.599981 377.163903
24 13312.0 494.180982 406.473303 377.645399
25 13824.0 482.934503 412.656711 379.389355
26 14336.0 471.967074 402.414053 370.558967
27 14848.0 461.297068 406.794504 373.534584
28 15360.0 454.269882 406.214870 377.511515
29 15872.0 447.098578 407.627589 376.225175
@@ -393,7 +393,7 @@ Layer Normalization
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 5 minutes 35.089 seconds)
**Total running time of the script:** ( 5 minutes 37.451 seconds)
.. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:

View File

@@ -385,7 +385,7 @@ This is a Triton implementation of the Flash Attention algorithm
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 0.072 seconds)
**Total running time of the script:** ( 0 minutes 0.073 seconds)
.. _sphx_glr_download_getting-started_tutorials_06-fused-attention.py:

View File

@@ -152,7 +152,7 @@ We can also customize the libdevice library path by passing the path to the `lib
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 0.010 seconds)
**Total running time of the script:** ( 0 minutes 0.254 seconds)
.. _sphx_glr_download_getting-started_tutorials_07-libdevice-function.py:

View File

@@ -5,20 +5,20 @@
Computation times
=================
**17:23.779** total execution time for **getting-started_tutorials** files:
**18:18.630** total execution time for **getting-started_tutorials** files:
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:37.798 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 07:19.813 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 05:35.089 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 05:37.451 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:28.967 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:32.036 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:41.831 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:48.722 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``) | 00:00.072 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.281 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.012 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_07-libdevice-function.py` (``07-libdevice-function.py``) | 00:00.254 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_getting-started_tutorials_07-libdevice-function.py` (``07-libdevice-function.py``) | 00:00.010 | 0.0 MB |
| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``) | 00:00.073 | 0.0 MB |
+---------------------------------------------------------------------------------------------------------+-----------+--------+

View File

@@ -325,24 +325,24 @@ for different problem sizes.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector-add-performance:
size Triton Torch
0 4096.0 9.600000 9.600000
1 8192.0 19.200000 15.999999
1 8192.0 19.200000 19.200000
2 16384.0 38.400001 38.400001
3 32768.0 76.800002 76.800002
4 65536.0 127.999995 127.999995
5 131072.0 219.428568 219.428568
6 262144.0 384.000001 384.000001
6 262144.0 341.333321 384.000001
7 524288.0 472.615390 472.615390
8 1048576.0 614.400016 614.400016
9 2097152.0 722.823517 722.823517
10 4194304.0 780.190482 780.190482
11 8388608.0 812.429770 812.429770
12 16777216.0 833.084721 833.084721
13 33554432.0 842.004273 842.004273
13 33554432.0 842.004273 843.811163
14 67108864.0 847.448255 848.362445
15 134217728.0 849.737435 850.656574
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 41.831 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 48.722 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>

View File

@@ -371,17 +371,17 @@ We will then compare its performance against (1) <code class="code docutils lite
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>softmax-performance:
N Triton Torch (native) Torch (jit)
0 256.0 546.133347 546.133347 190.511628
1 384.0 614.400016 585.142862 151.703707
2 512.0 655.360017 606.814814 156.038096
0 256.0 512.000001 546.133347 186.181817
1 384.0 614.400016 585.142862 153.600004
2 512.0 655.360017 585.142849 154.566038
3 640.0 706.206879 640.000002 160.000000
4 768.0 722.823517 664.216187 163.839992
.. ... ... ... ...
93 12160.0 812.359066 405.333344 199.038365
94 12288.0 812.429770 415.222812 199.197579
95 12416.0 812.498981 411.296057 198.805107
96 12544.0 811.745227 412.971190 199.012395
97 12672.0 811.007961 412.097543 199.167004
93 12160.0 812.359066 405.755985 198.936606
94 12288.0 812.429770 415.661740 199.197579
95 12416.0 812.498981 411.722274 198.755369
96 12544.0 810.925276 412.971190 199.012395
97 12672.0 811.007961 412.097543 199.069228
[98 rows x 4 columns]
</pre></div>
@@ -394,7 +394,7 @@ We will then compare its performance against (1) <code class="code docutils lite
Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li>
</ul>
</div></blockquote>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 28.967 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 32.036 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>

View File

@@ -567,42 +567,42 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
M cuBLAS ... Triton Triton (+ LeakyReLU)
0 256.0 2.978909 ... 3.276800 3.276800
0 256.0 2.730667 ... 2.978909 3.276800
1 384.0 7.372800 ... 8.507077 8.507077
2 512.0 14.563555 ... 16.384000 16.384000
2 512.0 14.563555 ... 16.384000 15.420235
3 640.0 22.260869 ... 24.380953 24.380953
4 768.0 32.768000 ... 35.389441 34.028308
5 896.0 39.025776 ... 40.140799 39.025776
6 1024.0 49.932191 ... 53.773130 52.428801
5 896.0 37.971025 ... 40.140799 39.025776
6 1024.0 49.932191 ... 53.773130 53.092457
7 1152.0 45.242181 ... 48.161033 48.161033
8 1280.0 51.200001 ... 57.690139 57.690139
9 1408.0 64.138541 ... 69.009825 68.147202
9 1408.0 64.138541 ... 69.009825 67.305878
10 1536.0 80.430545 ... 81.355034 79.526831
11 1664.0 63.372618 ... 63.372618 62.492442
12 1792.0 72.983276 ... 73.460287 59.467852
11 1664.0 62.929456 ... 63.372618 62.492442
12 1792.0 72.512412 ... 73.460287 59.467852
13 1920.0 69.120002 ... 71.626943 71.257735
14 2048.0 73.908442 ... 78.398206 77.314362
15 2176.0 83.500614 ... 87.876193 86.367588
15 2176.0 83.500614 ... 87.876193 85.998493
16 2304.0 68.446623 ... 78.064941 77.057651
17 2432.0 71.305746 ... 85.915795 83.366361
18 2560.0 77.833728 ... 81.715711 81.310171
19 2688.0 83.369354 ... 90.532356 90.102270
20 2816.0 81.445766 ... 84.035084 83.873477
21 2944.0 81.564701 ... 83.477440 82.921853
22 3072.0 82.420822 ... 89.735509 88.750943
23 3200.0 84.544253 ... 97.116842 95.096582
24 3328.0 83.905938 ... 85.806075 83.808259
25 3456.0 82.773682 ... 90.180725 90.687926
26 3584.0 87.042978 ... 99.244365 98.268190
27 3712.0 81.482335 ... 88.718781 88.248537
28 3840.0 82.531346 ... 89.043476 89.912191
29 3968.0 86.911637 ... 92.652949 84.094627
30 4096.0 93.368854 ... 83.313299 89.928129
17 2432.0 71.305746 ... 85.393507 75.522751
18 2560.0 77.833728 ... 82.125311 80.908642
19 2688.0 83.922689 ... 90.966561 89.464755
20 2816.0 81.067298 ... 84.360174 83.873477
21 2944.0 81.967162 ... 83.337844 81.832567
22 3072.0 82.420822 ... 89.310890 88.473602
23 3200.0 83.879425 ... 95.238096 87.671229
24 3328.0 82.369902 ... 85.602017 81.994643
25 3456.0 80.864158 ... 84.332184 90.281712
26 3584.0 87.127323 ... 97.947050 97.205829
27 3712.0 84.159518 ... 89.035062 87.552452
28 3840.0 81.138664 ... 86.332554 90.279183
29 3968.0 87.913500 ... 91.954739 86.358055
30 4096.0 93.271527 ... 84.254693 82.418802
[31 rows x 5 columns]
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 6 minutes 37.798 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 7 minutes 19.813 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>

View File

@@ -374,7 +374,7 @@ to explore the <cite>triton/language/random</cite> folder!</p>
<dd><p>Nitish Srivastava and Geoffrey Hinton and Alex Krizhevsky and Ilya Sutskever and Ruslan Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting”, JMLR 2014</p>
</dd>
</dl>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.012 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.281 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-04-low-memory-dropout-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/c9aed78977a4c05741d675a38dde3d7d/04-low-memory-dropout.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">04-low-memory-dropout.py</span></code></a></p>

View File

@@ -196,34 +196,34 @@ to download the full example code</p>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>layer-norm:
N Triton Torch Apex
0 1024.0 585.142849 277.694907 468.114273
0 1024.0 606.814814 277.694907 468.114273
1 1536.0 630.153868 323.368435 511.999982
2 2048.0 668.734716 337.814445 520.126988
3 2560.0 694.237267 362.477870 518.481028
4 3072.0 712.347810 378.092307 501.551037
5 3584.0 725.873439 384.859062 458.751978
6 4096.0 728.177767 383.251446 455.111095
7 4608.0 670.254540 396.387087 423.724136
8 5120.0 688.403381 395.748783 417.959197
9 5632.0 704.000002 396.969169 413.357796
10 6144.0 702.171410 404.543206 409.600010
2 2048.0 682.666643 337.814445 520.126988
3 2560.0 694.237267 362.477870 512.000013
4 3072.0 712.347810 378.092307 506.721668
5 3584.0 725.873439 384.859062 455.111115
6 4096.0 728.177767 381.023256 451.972420
7 4608.0 670.254540 396.387087 431.157877
8 5120.0 688.403381 397.669909 422.268057
9 5632.0 704.000002 395.228063 415.262685
10 6144.0 702.171410 402.885254 409.600010
11 6656.0 700.631610 400.360920 400.360920
12 7168.0 690.891575 391.426634 387.459443
13 7680.0 678.895043 392.587863 385.203746
14 8192.0 636.271854 388.937680 368.179771
15 8704.0 627.315309 387.922008 380.502740
16 9216.0 606.814809 405.098894 382.010363
17 9728.0 587.350922 409.599987 382.427505
18 10240.0 566.920437 408.578556 382.803739
19 10752.0 547.872604 411.559798 380.601764
20 11264.0 533.207081 401.389743 372.363645
21 11776.0 520.486200 408.711507 377.587162
22 12288.0 516.031509 413.911572 383.251457
23 12800.0 504.433489 410.420828 377.163903
24 13312.0 494.180982 404.159395 375.647260
25 13824.0 482.934503 410.359948 378.739711
26 14336.0 472.940209 403.121247 374.185964
27 14848.0 461.297068 405.406157 374.712936
12 7168.0 690.891575 392.767108 382.293315
13 7680.0 678.895043 393.846167 386.415087
14 8192.0 633.198054 394.795186 376.643677
15 8704.0 624.502255 389.005597 379.465939
16 9216.0 606.814809 406.214877 382.010363
17 9728.0 587.350922 408.524944 383.369452
18 10240.0 564.965524 409.600010 382.803739
19 10752.0 546.133312 411.559798 380.601764
20 11264.0 532.419472 404.089694 371.595879
21 11776.0 520.486200 409.599991 377.587162
22 12288.0 513.336807 413.911572 383.251457
23 12800.0 504.433489 409.599981 377.163903
24 13312.0 494.180982 406.473303 377.645399
25 13824.0 482.934503 412.656711 379.389355
26 14336.0 471.967074 402.414053 370.558967
27 14848.0 461.297068 406.794504 373.534584
28 15360.0 454.269882 406.214870 377.511515
29 15872.0 447.098578 407.627589 376.225175
</pre></div>
@@ -543,7 +543,7 @@ to download the full example code</p>
<span class="n">bench_layer_norm</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">save_path</span><span class="o">=</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="n">print_data</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 35.089 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 37.451 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-05-layer-norm-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/935c0dd0fbeb4b2e69588471cbb2d4b2/05-layer-norm.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">05-layer-norm.py</span></code></a></p>

View File

@@ -543,7 +543,7 @@ to download the full example code</p>
<span class="c1"># bench_flash_attention.run(save_path=&#39;.&#39;, print_data=True)</span>
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.072 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.073 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-06-fused-attention-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/54a35f6ec55f9746935b9566fb6bb1df/06-fused-attention.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">06-fused-attention.py</span></code></a></p>

View File

@@ -276,7 +276,7 @@ tensor([0.4105, 0.5430, 0.0249, ..., 0.0424, 0.5351, 0.8149], device=&#39;cuda:
The maximum difference between torch and triton is 2.384185791015625e-07
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.010 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.254 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-07-libdevice-function-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/3ff29f967ace7985da24aab10352fc76/07-libdevice-function.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">07-libdevice-function.py</span></code></a></p>

View File

@@ -174,7 +174,7 @@
<div class="section" id="computation-times">
<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>
<p><strong>17:23.779</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<p><strong>18:18.630</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 85%" />
@@ -183,31 +183,31 @@
</colgroup>
<tbody>
<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>06:37.798</p></td>
<td><p>07:19.813</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="05-layer-norm.html#sphx-glr-getting-started-tutorials-05-layer-norm-py"><span class="std std-ref">Layer Normalization</span></a> (<code class="docutils literal notranslate"><span class="pre">05-layer-norm.py</span></code>)</p></td>
<td><p>05:35.089</p></td>
<td><p>05:37.451</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><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>03:28.967</p></td>
<td><p>03:32.036</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><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>01:41.831</p></td>
<td><p>01:48.722</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="04-low-memory-dropout.html#sphx-glr-getting-started-tutorials-04-low-memory-dropout-py"><span class="std std-ref">Low-Memory Dropout</span></a> (<code class="docutils literal notranslate"><span class="pre">04-low-memory-dropout.py</span></code>)</p></td>
<td><p>00:00.281</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="07-libdevice-function.html#sphx-glr-getting-started-tutorials-07-libdevice-function-py"><span class="std std-ref">Libdevice function</span></a> (<code class="docutils literal notranslate"><span class="pre">07-libdevice-function.py</span></code>)</p></td>
<td><p>00:00.254</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="06-fused-attention.html#sphx-glr-getting-started-tutorials-06-fused-attention-py"><span class="std std-ref">Fused Attention</span></a> (<code class="docutils literal notranslate"><span class="pre">06-fused-attention.py</span></code>)</p></td>
<td><p>00:00.072</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="04-low-memory-dropout.html#sphx-glr-getting-started-tutorials-04-low-memory-dropout-py"><span class="std std-ref">Low-Memory Dropout</span></a> (<code class="docutils literal notranslate"><span class="pre">04-low-memory-dropout.py</span></code>)</p></td>
<td><p>00:00.012</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="07-libdevice-function.html#sphx-glr-getting-started-tutorials-07-libdevice-function-py"><span class="std std-ref">Libdevice function</span></a> (<code class="docutils literal notranslate"><span class="pre">07-libdevice-function.py</span></code>)</p></td>
<td><p>00:00.010</p></td>
<td><p>00:00.073</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>

File diff suppressed because one or more lines are too long

View File

@@ -1,4 +1,4 @@
# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 784411d4b02c2349600353c604bdc5fb
config: a3a64108ca8bf37686e8d499a663d6f4
tags: 645f666f9bcd5a90fca523b33c5a78b7

Binary file not shown.

Binary file not shown.

Some files were not shown because too many files have changed in this diff Show More