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@@ -255,7 +255,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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.. rst-class:: sphx-glr-timing
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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@@ -393,7 +393,7 @@ Layer Normalization
|
||||
|
||||
.. rst-class:: sphx-glr-timing
|
||||
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**Total running time of the script:** ( 5 minutes 37.670 seconds)
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**Total running time of the script:** ( 5 minutes 37.042 seconds)
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||||
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||||
.. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:
|
||||
|
@@ -385,7 +385,7 @@ This is a Triton implementation of the Flash Attention algorithm
|
||||
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||||
.. rst-class:: sphx-glr-timing
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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 0.254 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
|
||||
=================
|
||||
**17:32.005** total execution time for **getting-started_tutorials** files:
|
||||
**18:15.037** total execution time for **getting-started_tutorials** files:
|
||||
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:37.352 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 07:16.663 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 05:37.670 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``) | 05:37.042 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:30.609 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:30.792 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:46.276 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:49.928 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``) | 00:00.073 | 0.0 MB |
|
||||
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.279 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.014 | 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``) | 00:00.078 | 0.0 MB |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
|
@@ -327,22 +327,22 @@ for different problem sizes.</p>
|
||||
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|
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||||
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|
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|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 46.276 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 49.928 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>
|
||||
|
@@ -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)
|
||||
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|
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1 384.0 614.400016 585.142862 151.703707
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||||
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|
||||
3 640.0 706.206879 640.000002 158.759699
|
||||
0 256.0 546.133347 546.133347 188.321838
|
||||
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|
||||
2 512.0 655.360017 606.814814 154.566038
|
||||
3 640.0 706.206879 640.000002 160.000000
|
||||
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|
||||
.. ... ... ... ...
|
||||
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||||
93 12160.0 812.359066 406.179533 198.834951
|
||||
94 12288.0 812.429770 415.661740 199.197579
|
||||
95 12416.0 812.498981 412.149375 198.755369
|
||||
96 12544.0 810.925276 412.971190 198.963085
|
||||
97 12672.0 811.007961 412.516771 199.069228
|
||||
96 12544.0 810.925276 412.971190 199.012395
|
||||
97 12672.0 811.007961 412.097543 199.167004
|
||||
|
||||
[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 30.609 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 30.792 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
|
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<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>
|
||||
|
@@ -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)
|
||||
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|
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1 384.0 7.372800 ... 8.507077 7.899428
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||||
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||||
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|
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|
||||
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|
||||
7 1152.0 45.242181 ... 48.161033 47.396572
|
||||
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
|
||||
10 1536.0 80.430545 ... 80.430545 79.526831
|
||||
9 1408.0 64.138541 ... 69.009825 67.305878
|
||||
10 1536.0 80.430545 ... 81.355034 79.526831
|
||||
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|
||||
12 1792.0 72.512412 ... 73.460287 59.467852
|
||||
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|
||||
13 1920.0 68.776119 ... 71.257735 71.257735
|
||||
14 2048.0 73.908442 ... 78.398206 77.314362
|
||||
15 2176.0 83.500614 ... 87.876193 86.367588
|
||||
16 2304.0 68.251065 ... 77.810656 77.307030
|
||||
17 2432.0 71.305746 ... 84.367759 75.320281
|
||||
18 2560.0 78.019048 ... 82.539044 81.310171
|
||||
19 2688.0 83.552988 ... 90.316801 89.254248
|
||||
20 2816.0 79.154642 ... 83.873477 83.712490
|
||||
21 2944.0 82.784108 ... 83.617504 83.337844
|
||||
22 3072.0 81.707223 ... 86.978653 88.750943
|
||||
23 3200.0 82.262212 ... 92.086332 87.611228
|
||||
24 3328.0 81.622783 ... 83.808259 82.181847
|
||||
25 3456.0 81.849303 ... 88.207407 90.281712
|
||||
26 3584.0 86.874778 ... 98.483450 98.483450
|
||||
27 3712.0 81.615477 ... 89.114488 87.629253
|
||||
28 3840.0 81.919998 ... 88.121115 90.389865
|
||||
29 3968.0 86.973584 ... 91.954739 86.053553
|
||||
30 4096.0 93.401342 ... 83.106955 88.709668
|
||||
16 2304.0 68.446623 ... 77.810656 77.307030
|
||||
17 2432.0 71.305746 ... 86.711310 85.653855
|
||||
18 2560.0 77.833728 ... 82.956960 81.108913
|
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19 2688.0 83.369354 ... 90.316801 90.102270
|
||||
20 2816.0 79.587973 ... 84.687779 83.153880
|
||||
21 2944.0 81.967162 ... 83.617504 81.967162
|
||||
22 3072.0 81.707223 ... 90.020831 88.060814
|
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23 3200.0 83.879425 ... 95.238096 87.673110
|
||||
24 3328.0 83.226931 ... 82.748617 84.895397
|
||||
25 3456.0 81.353753 ... 88.207407 91.200871
|
||||
26 3584.0 87.296493 ... 99.354022 97.628001
|
||||
27 3712.0 82.421427 ... 89.353616 83.247783
|
||||
28 3840.0 83.339866 ... 91.398346 86.840987
|
||||
29 3968.0 86.849777 ... 92.302520 84.066569
|
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30 4096.0 93.077479 ... 83.055527 82.340585
|
||||
|
||||
[31 rows x 5 columns]
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 6 minutes 37.352 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 7 minutes 16.663 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-03-matrix-multiplication-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<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>
|
||||
|
@@ -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>
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</dd>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.014 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.279 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-04-low-memory-dropout-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<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>
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|
@@ -196,36 +196,36 @@ to download the full example code</p>
|
||||
<p class="sphx-glr-script-out">Out:</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>layer-norm:
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N Triton Torch Apex
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0 1024.0 585.142849 277.694907 481.882344
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1 1536.0 630.153868 323.368435 511.999982
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4 3072.0 712.347810 376.643666 501.551037
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5 3584.0 725.873439 384.859062 455.111115
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6 4096.0 728.177767 381.023256 451.972420
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7 4608.0 670.254540 396.387087 428.651163
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8 5120.0 688.403381 395.748783 422.268057
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16 9216.0 606.814809 406.214877 382.010363
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17 9728.0 587.350922 408.524944 382.427505
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18 10240.0 566.920437 409.600010 382.803739
|
||||
19 10752.0 547.872604 410.577576 380.601764
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20 11264.0 533.207081 399.609756 370.069806
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||||
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||||
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||||
9 5632.0 698.542675 395.228063 413.357796
|
||||
10 6144.0 702.171410 402.885254 411.313806
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12 7168.0 690.891575 396.844306 387.459443
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18 10240.0 564.965524 408.578556 382.803739
|
||||
19 10752.0 547.872604 411.559798 381.445676
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||||
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|
||||
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||||
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|
||||
23 12800.0 504.433489 409.599981 376.470582
|
||||
24 13312.0 494.180982 403.393936 376.976995
|
||||
25 13824.0 482.934503 411.888257 379.389355
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||||
26 14336.0 471.967074 401.709294 374.797384
|
||||
27 14848.0 461.297068 407.492270 374.712936
|
||||
28 15360.0 454.269882 406.887417 378.092307
|
||||
29 15872.0 447.098578 406.323209 376.225175
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||||
22 12288.0 514.680630 413.911572 383.251457
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||||
23 12800.0 504.433489 410.420828 376.470582
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||||
24 13312.0 494.180982 405.699062 376.310952
|
||||
25 13824.0 481.882350 411.888257 379.389355
|
||||
26 14336.0 470.997935 406.695045 374.185964
|
||||
27 14848.0 460.403127 408.192434 374.712936
|
||||
28 15360.0 454.269882 406.214870 378.092307
|
||||
29 15872.0 447.887117 406.974373 376.225175
|
||||
</pre></div>
|
||||
</div>
|
||||
<div class="line-block">
|
||||
@@ -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">'.'</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 37.670 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 37.042 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>
|
||||
|
@@ -543,7 +543,7 @@ to download the full example code</p>
|
||||
<span class="c1"># bench_flash_attention.run(save_path='.', print_data=True)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.073 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.078 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>
|
||||
|
@@ -276,7 +276,7 @@ tensor([0.4105, 0.5430, 0.0249, ..., 0.0424, 0.5351, 0.8149], device='cuda:
|
||||
The maximum difference between torch and triton is 2.384185791015625e-07
|
||||
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||||
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|
||||
<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>
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<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>
|
||||
|
@@ -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>17:32.005</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>18:15.037</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>06:37.352</p></td>
|
||||
<td><p>07:16.663</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>05:37.670</p></td>
|
||||
<td><p>05:37.042</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
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</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>03:30.609</p></td>
|
||||
<td><p>03:30.792</p></td>
|
||||
<td><p>0.0 MB</p></td>
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</tr>
|
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<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>01:46.276</p></td>
|
||||
<td><p>01:49.928</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
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</tr>
|
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<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>00:00.279</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>
|
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<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>00:00.073</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>00:00.014</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
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||||
<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>
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||||
<td><p>00:00.010</p></td>
|
||||
<td><p>00:00.078</p></td>
|
||||
<td><p>0.0 MB</p></td>
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||||
</tr>
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||||
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||||
|
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# Sphinx build info version 1
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||||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: d6e59d79e230a7dfa4c0f8e03193953c
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config: 5ff844b60fe8ebfd1a1440ce778cb355
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tags: 645f666f9bcd5a90fca523b33c5a78b7
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