[GH-PAGES] Updated website

master/.buildinfo

@@ -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: 8690d986c60dfaae2451e682bbdc6e34
+config: 4e6a6a46ebd09a395d46365c942efe4a
 tags: 645f666f9bcd5a90fca523b33c5a78b7

master/_sources/getting-started/tutorials/01-vector-add.rst.txt

@@ -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   76.800002   76.800002
     4       65536.0  127.999995  127.999995
     5      131072.0  219.428568  219.428568
     6      262144.0  341.333321  384.000001
@@ -245,7 +245,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
     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  38.414 seconds)
+   **Total running time of the script:** ( 1 minutes  42.825 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:

master/_sources/getting-started/tutorials/02-fused-softmax.rst.txt

@@ -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   186.181817
-    1     384.0  585.142862      585.142862   151.703707
-    2     512.0  655.360017      606.814814   156.038096
-    3     640.0  682.666684      640.000002   160.000000
-    4     768.0  722.823517      664.216187   163.839992
+    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      405.755985   198.834951
-    94  12288.0  814.111783      415.222812   199.096718
-    95  12416.0  814.163950      411.296057   198.755369
-    96  12544.0  814.214963      412.546756   198.864492
-    97  12672.0  814.265046      412.097543   199.069228
+    93  12160.0  815.765209      406.179533   198.631953
+    94  12288.0  815.800825      415.661740   198.895304
+    95  12416.0  814.163950      412.149375   198.457532
+    96  12544.0  814.214963      412.971190   198.716830
+    97  12672.0  814.265046      411.679167   198.679085
 
     [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  19.681 seconds)
+   **Total running time of the script:** ( 3 minutes  22.274 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:

master/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt

@@ -459,36 +459,36 @@ 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
-    1    384.0   7.372800  ...   8.507077              7.899428
+    1    384.0   7.372800  ...   8.507077              8.192000
     2    512.0  14.563555  ...  16.384000             16.384000
-    3    640.0  23.272727  ...  24.380953             24.380953
+    3    640.0  22.260869  ...  24.380953             24.380953
     4    768.0  32.768000  ...  34.028308             34.028308
-    5    896.0  37.971025  ...  40.140799             39.025776
+    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             62.492442
-    12  1792.0  72.512412  ...  72.047592             72.047592
-    13  1920.0  68.776119  ...  70.172588             70.530615
-    14  2048.0  73.584279  ...  76.608294             76.608294
-    15  2176.0  83.500614  ...  86.367588             85.998493
-    16  2304.0  68.643310  ...  76.809875             76.563695
-    17  2432.0  71.487187  ...  74.719317             84.621881
-    18  2560.0  77.283019  ...  81.108913             81.108913
-    19  2688.0  83.369354  ...  89.464755             89.676257
-    20  2816.0  81.981598  ...  83.392363             82.916747
-    21  2944.0  81.967162  ...  81.034195             81.832567
-    22  3072.0  82.301023  ...  87.924073             88.612060
-    23  3200.0  78.816219  ...  94.814812             95.380032
-    24  3328.0  84.101981  ...  82.275764             85.500351
-    25  3456.0  81.849303  ...  83.893412             90.281712
-    26  3584.0  87.211821  ...  98.537414             90.367227
-    27  3712.0  80.627396  ...  87.132441             87.018592
-    28  3840.0  84.940091  ...  92.236860             84.548438
-    29  3968.0  92.302520  ...  84.154440             90.724116
-    30  4096.0  86.478753  ...  90.169784             87.097813
+    10  1536.0  79.526831  ...  79.526831             78.643199
+    11  1664.0  62.929456  ...  62.492442             62.061463
+    12  1792.0  72.512412  ...  71.588687             72.047592
+    13  1920.0  69.120002  ...  70.172588             70.172588
+    14  2048.0  73.908442  ...  76.959706             76.260072
+    15  2176.0  83.155572  ...  85.998493             85.998493
+    16  2304.0  68.643310  ...  76.809875             76.076024
+    17  2432.0  71.125224  ...  84.877538             85.134737
+    18  2560.0  78.019048  ...  80.908642             81.108913
+    19  2688.0  82.642823  ...  89.995386             89.464755
+    20  2816.0  83.074685  ...  83.552120             82.680963
+    21  2944.0  81.832567  ...  81.564701             81.967162
+    22  3072.0  81.707223  ...  88.060814             88.612060
+    23  3200.0  80.706181  ...  95.167286             94.814812
+    24  3328.0  83.226931  ...  84.003845             84.298943
+    25  3456.0  79.430113  ...  84.909497             89.380896
+    26  3584.0  87.466332  ...  97.734120             98.160909
+    27  3712.0  79.917877  ...  86.942857             89.035062
+    28  3840.0  84.292684  ...  91.473945             86.467555
+    29  3968.0  90.791620  ...  80.864108             86.572497
+    30  4096.0  88.592559  ...  86.928580             91.366730
 
     [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:** ( 5 minutes  57.081 seconds)
+   **Total running time of the script:** ( 6 minutes  8.357 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:

master/_sources/getting-started/tutorials/04-low-memory-dropout.rst.txt

@@ -240,7 +240,7 @@ References
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  0.497 seconds)
+   **Total running time of the script:** ( 0 minutes  0.489 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:

master/_sources/getting-started/tutorials/05-layer-norm.rst.txt

@@ -38,36 +38,36 @@ Layer Normalization
 
     layer-norm-backward:
               N      Triton       Torch        Apex
-    0    1024.0  307.200008   97.912354  303.407414
+    0    1024.0  311.088617   98.303995  307.200008
     1    1536.0  347.773587  134.540150  341.333333
-    2    2048.0  420.102553  161.684218  323.368435
-    3    2560.0  458.507457  181.238943  330.322572
+    2    2048.0  420.102553  161.684218  334.367350
+    3    2560.0  458.507457  181.775141  330.322572
     4    3072.0  511.999982  192.501302  320.556515
-    5    3584.0  547.872604  208.271186  312.785456
-    6    4096.0  568.231237  220.907859  300.623865
-    7    4608.0  507.302750  232.825259  287.999990
-    8    5120.0  527.381977  242.845844  285.104413
-    9    5632.0  540.671974  241.371422  288.204696
-    10   6144.0  548.163546  250.349744  287.438593
-    11   6656.0  534.260858  256.000009  286.279570
-    12   7168.0  512.000004  255.240352  280.182402
-    13   7680.0  485.052616  263.690977  277.172933
-    14   8192.0  463.698115  268.223740  281.673345
-    15   8704.0  418.629245  266.109560  282.291896
-    16   9216.0  432.845409  272.394084  288.375482
-    17   9728.0  439.683593  278.606213  287.173424
-    18  10240.0  446.025405  286.767793  288.112552
-    19  10752.0  423.724151  244.827326  288.321786
-    20  11264.0  426.397479  245.983625  287.285864
-    21  11776.0  421.198220  247.807112  287.219500
-    22  12288.0  420.701865  254.453844  294.911986
-    23  12800.0  413.458944  252.009851  287.910035
-    24  13312.0  411.181478  253.763296  290.972683
-    25  13824.0  403.620451  258.191439  292.829653
-    26  14336.0  394.116833  255.240352  289.372589
-    27  14848.0  385.245405  256.552919  289.952797
-    28  15360.0  379.649845  262.751252  289.811315
-    29  15872.0  370.913333  261.806182  289.899545
+    5    3584.0  547.872604  208.271186  311.652167
+    6    4096.0  568.231237  220.412561  297.890900
+    7    4608.0  504.986315  232.825259  286.507772
+    8    5120.0  529.655159  242.845844  285.104413
+    9    5632.0  545.032265  243.545956  289.438969
+    10   6144.0  548.163546  248.661056  285.767458
+    11   6656.0  534.260858  256.000009  285.767438
+    12   7168.0  507.469040  260.457220  286.242939
+    13   7680.0  481.253256  262.190612  275.104486
+    14   8192.0  462.607053  267.130429  284.939124
+    15   8704.0  417.791980  267.815384  284.599455
+    16   9216.0  431.157889  272.394084  288.751954
+    17   9728.0  438.857162  280.615388  290.027323
+    18  10240.0  449.287041  286.433562  287.438599
+    19  10752.0  427.231788  247.172406  290.594591
+    20  11264.0  427.071098  245.760001  286.676558
+    21  11776.0  422.457417  249.667843  288.686414
+    22  12288.0  419.504980  254.453844  294.029924
+    23  12800.0  414.016170  253.256381  289.538159
+    24  13312.0  411.181478  252.759501  289.916513
+    25  13824.0  404.112047  257.190689  292.056329
+    26  14336.0  393.215988  254.485198  286.719986
+    27  14848.0  385.245405  257.665934  289.246765
+    28  15360.0  373.495460  257.970599  287.102804
+    29  15872.0  371.637071  261.806182  289.899545
 
 
 
@@ -339,7 +339,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  12.137 seconds)
+   **Total running time of the script:** ( 2 minutes  12.324 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:

master/_sources/getting-started/tutorials/sg_execution_times.rst.txt

@@ -5,16 +5,16 @@
 
 Computation times
 =================
-**13:07.810** total execution time for **getting-started_tutorials** files:
+**13:26.269** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:57.081 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:08.357 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:19.681 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:22.274 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:12.137 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:12.324 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:38.414 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:42.825 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.497 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.489 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

master/getting-started/tutorials/01-vector-add.html

@@ -325,7 +325,7 @@ for different problem sizes.</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   76.800002   76.800002
 4       65536.0  127.999995  127.999995
 5      131072.0  219.428568  219.428568
 6      262144.0  341.333321  384.000001
@@ -335,12 +335,12 @@ for different problem sizes.</p>
 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  38.414 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  42.825 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>

master/getting-started/tutorials/02-fused-softmax.html

@@ -369,17 +369,17 @@ 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   186.181817
-1     384.0  585.142862      585.142862   151.703707
-2     512.0  655.360017      606.814814   156.038096
-3     640.0  682.666684      640.000002   160.000000
-4     768.0  722.823517      664.216187   163.839992
+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      405.755985   198.834951
-94  12288.0  814.111783      415.222812   199.096718
-95  12416.0  814.163950      411.296057   198.755369
-96  12544.0  814.214963      412.546756   198.864492
-97  12672.0  814.265046      412.097543   199.069228
+93  12160.0  815.765209      406.179533   198.631953
+94  12288.0  815.800825      415.661740   198.895304
+95  12416.0  814.163950      412.149375   198.457532
+96  12544.0  814.214963      412.971190   198.716830
+97  12672.0  814.265046      411.679167   198.679085
 
 [98 rows x 4 columns]
 </pre></div>
@@ -392,7 +392,7 @@ 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  19.681 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  22.274 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>

master/getting-started/tutorials/03-matrix-multiplication.html

@@ -565,41 +565,41 @@ torch_output=tensor([[  1.1045, -36.9688,  31.4688,  ..., -11.3906,  24.4531, -3
 <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  ...   2.978909              2.978909
-1    384.0   7.372800  ...   8.507077              7.899428
+1    384.0   7.372800  ...   8.507077              8.192000
 2    512.0  14.563555  ...  16.384000             16.384000
-3    640.0  23.272727  ...  24.380953             24.380953
+3    640.0  22.260869  ...  24.380953             24.380953
 4    768.0  32.768000  ...  34.028308             34.028308
-5    896.0  37.971025  ...  40.140799             39.025776
+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             62.492442
-12  1792.0  72.512412  ...  72.047592             72.047592
-13  1920.0  68.776119  ...  70.172588             70.530615
-14  2048.0  73.584279  ...  76.608294             76.608294
-15  2176.0  83.500614  ...  86.367588             85.998493
-16  2304.0  68.643310  ...  76.809875             76.563695
-17  2432.0  71.487187  ...  74.719317             84.621881
-18  2560.0  77.283019  ...  81.108913             81.108913
-19  2688.0  83.369354  ...  89.464755             89.676257
-20  2816.0  81.981598  ...  83.392363             82.916747
-21  2944.0  81.967162  ...  81.034195             81.832567
-22  3072.0  82.301023  ...  87.924073             88.612060
-23  3200.0  78.816219  ...  94.814812             95.380032
-24  3328.0  84.101981  ...  82.275764             85.500351
-25  3456.0  81.849303  ...  83.893412             90.281712
-26  3584.0  87.211821  ...  98.537414             90.367227
-27  3712.0  80.627396  ...  87.132441             87.018592
-28  3840.0  84.940091  ...  92.236860             84.548438
-29  3968.0  92.302520  ...  84.154440             90.724116
-30  4096.0  86.478753  ...  90.169784             87.097813
+10  1536.0  79.526831  ...  79.526831             78.643199
+11  1664.0  62.929456  ...  62.492442             62.061463
+12  1792.0  72.512412  ...  71.588687             72.047592
+13  1920.0  69.120002  ...  70.172588             70.172588
+14  2048.0  73.908442  ...  76.959706             76.260072
+15  2176.0  83.155572  ...  85.998493             85.998493
+16  2304.0  68.643310  ...  76.809875             76.076024
+17  2432.0  71.125224  ...  84.877538             85.134737
+18  2560.0  78.019048  ...  80.908642             81.108913
+19  2688.0  82.642823  ...  89.995386             89.464755
+20  2816.0  83.074685  ...  83.552120             82.680963
+21  2944.0  81.832567  ...  81.564701             81.967162
+22  3072.0  81.707223  ...  88.060814             88.612060
+23  3200.0  80.706181  ...  95.167286             94.814812
+24  3328.0  83.226931  ...  84.003845             84.298943
+25  3456.0  79.430113  ...  84.909497             89.380896
+26  3584.0  87.466332  ...  97.734120             98.160909
+27  3712.0  79.917877  ...  86.942857             89.035062
+28  3840.0  84.292684  ...  91.473945             86.467555
+29  3968.0  90.791620  ...  80.864108             86.572497
+30  4096.0  88.592559  ...  86.928580             91.366730
 
 [31 rows x 5 columns]
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes  57.081 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 6 minutes  8.357 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>

master/getting-started/tutorials/04-low-memory-dropout.html

@@ -372,7 +372,7 @@ 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  0.497 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  0.489 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>

master/getting-started/tutorials/05-layer-norm.html

@@ -194,36 +194,36 @@ 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-backward:
           N      Triton       Torch        Apex
-0    1024.0  307.200008   97.912354  303.407414
+0    1024.0  311.088617   98.303995  307.200008
 1    1536.0  347.773587  134.540150  341.333333
-2    2048.0  420.102553  161.684218  323.368435
-3    2560.0  458.507457  181.238943  330.322572
+2    2048.0  420.102553  161.684218  334.367350
+3    2560.0  458.507457  181.775141  330.322572
 4    3072.0  511.999982  192.501302  320.556515
-5    3584.0  547.872604  208.271186  312.785456
-6    4096.0  568.231237  220.907859  300.623865
-7    4608.0  507.302750  232.825259  287.999990
-8    5120.0  527.381977  242.845844  285.104413
-9    5632.0  540.671974  241.371422  288.204696
-10   6144.0  548.163546  250.349744  287.438593
-11   6656.0  534.260858  256.000009  286.279570
-12   7168.0  512.000004  255.240352  280.182402
-13   7680.0  485.052616  263.690977  277.172933
-14   8192.0  463.698115  268.223740  281.673345
-15   8704.0  418.629245  266.109560  282.291896
-16   9216.0  432.845409  272.394084  288.375482
-17   9728.0  439.683593  278.606213  287.173424
-18  10240.0  446.025405  286.767793  288.112552
-19  10752.0  423.724151  244.827326  288.321786
-20  11264.0  426.397479  245.983625  287.285864
-21  11776.0  421.198220  247.807112  287.219500
-22  12288.0  420.701865  254.453844  294.911986
-23  12800.0  413.458944  252.009851  287.910035
-24  13312.0  411.181478  253.763296  290.972683
-25  13824.0  403.620451  258.191439  292.829653
-26  14336.0  394.116833  255.240352  289.372589
-27  14848.0  385.245405  256.552919  289.952797
-28  15360.0  379.649845  262.751252  289.811315
-29  15872.0  370.913333  261.806182  289.899545
+5    3584.0  547.872604  208.271186  311.652167
+6    4096.0  568.231237  220.412561  297.890900
+7    4608.0  504.986315  232.825259  286.507772
+8    5120.0  529.655159  242.845844  285.104413
+9    5632.0  545.032265  243.545956  289.438969
+10   6144.0  548.163546  248.661056  285.767458
+11   6656.0  534.260858  256.000009  285.767438
+12   7168.0  507.469040  260.457220  286.242939
+13   7680.0  481.253256  262.190612  275.104486
+14   8192.0  462.607053  267.130429  284.939124
+15   8704.0  417.791980  267.815384  284.599455
+16   9216.0  431.157889  272.394084  288.751954
+17   9728.0  438.857162  280.615388  290.027323
+18  10240.0  449.287041  286.433562  287.438599
+19  10752.0  427.231788  247.172406  290.594591
+20  11264.0  427.071098  245.760001  286.676558
+21  11776.0  422.457417  249.667843  288.686414
+22  12288.0  419.504980  254.453844  294.029924
+23  12800.0  414.016170  253.256381  289.538159
+24  13312.0  411.181478  252.759501  289.916513
+25  13824.0  404.112047  257.190689  292.056329
+26  14336.0  393.215988  254.485198  286.719986
+27  14848.0  385.245405  257.665934  289.246765
+28  15360.0  373.495460  257.970599  287.102804
+29  15872.0  371.637071  261.806182  289.899545
 </pre></div>
 </div>
 <div class="line-block">
@@ -487,7 +487,7 @@ 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> ( 2 minutes  12.137 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes  12.324 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>

master/getting-started/tutorials/sg_execution_times.html

@@ -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>13:07.810</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
+<p><strong>13:26.269</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 85%" />
@@ -183,23 +183,23 @@
 </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>05:57.081</p></td>
+<td><p>06:08.357</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><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>03:19.681</p></td>
+<td><p>03:22.274</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-odd"><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>02:12.137</p></td>
+<td><p>02:12.324</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>01:38.414</p></td>
+<td><p>01:42.825</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>00:00.497</p></td>
+<td><p>00:00.489</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>

master/python-api/generated/triton.autotune.html

@@ -214,7 +214,7 @@ reset the value of the provided tensor to <cite>zero</cite> before running any c
 <li><p><strong>prune_configs_by</strong> – a dict of functions that are used to prune configs, fields:
 ‘perf_model’: performance model used to predicate running time with different configs, returns running time
 ‘top_k’: number of configs to bench
-‘prune_num_stages_by’(optional): a function used to prune num_stages. It take configs:List[Config] as its input, and returns pruned configs.</p></li>
+‘early_config_prune’(optional): a function used to do early prune (eg, num_stages). It take configs:List[Config] as its input, and returns pruned configs.</p></li>
 <li><p><strong>reset_to_zero</strong> (<em>list</em><em>[</em><em>str</em><em>]</em>) – a list of argument names whose value will be reset to zero before evaluating any configs.</p></li>
 </ul>
 </dd>

v1.1.2/.buildinfo

@@ -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: a230e6c1257ec5ebb8629f50dc3c50e6
+config: 641733a55f2ac5c24495e543792cb8a7
 tags: 645f666f9bcd5a90fca523b33c5a78b7