[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: a4ad4f0d97b54bd4b186ac06e193fef9
+config: d0253a34c4fed8d0f50aab31e68ccded
 tags: 645f666f9bcd5a90fca523b33c5a78b7

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

@@ -234,7 +234,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
                size      Triton       Torch
     0        4096.0    9.600000    9.600000
     1        8192.0   19.200000   19.200000
-    2       16384.0   31.999999   38.400001
+    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
@@ -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  40.596 seconds)
+   **Total running time of the script:** ( 1 minutes  48.582 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:

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

@@ -278,16 +278,16 @@ 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  546.133347      546.133347   188.321838
     1     384.0  585.142862      585.142862   151.703707
     2     512.0  655.360017      585.142849   156.038096
-    3     640.0  682.666684      640.000002   160.000000
-    4     768.0  722.823517      646.736871   163.839992
+    3     640.0  682.666684      640.000002   158.759699
+    4     768.0  722.823517      646.736871   162.754967
     ..      ...         ...             ...          ...
-    93  12160.0  814.058574      405.755985   198.936606
-    94  12288.0  815.800825      415.442160   199.197579
-    95  12416.0  814.163950      412.149375   198.854847
-    96  12544.0  814.214963      412.971190   199.012395
+    93  12160.0  814.058574      406.179533   198.834951
+    94  12288.0  814.111783      415.661740   199.096718
+    95  12416.0  814.163950      412.149375   198.755369
+    96  12544.0  814.214963      412.971190   198.913776
     97  12672.0  814.265046      412.097543   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  25.444 seconds)
+   **Total running time of the script:** ( 3 minutes  28.316 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   2.730667  ...   3.276800              2.978909
-    1    384.0   7.372800  ...   7.899428              7.899428
+    1    384.0   7.372800  ...   8.507077              8.507077
     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  37.971025  ...  40.140799             40.140799
+    5    896.0  37.971025  ...  41.321411             40.140799
     6   1024.0  49.932191  ...  53.773130             53.773130
     7   1152.0  44.566925  ...  48.161033             47.396572
     8   1280.0  51.200001  ...  57.690139             57.690139
     9   1408.0  64.138541  ...  69.009825             69.009825
-    10  1536.0  80.430545  ...  81.355034             80.430545
-    11  1664.0  62.929456  ...  63.372618             62.929456
-    12  1792.0  72.983276  ...  63.142831             62.790080
+    10  1536.0  80.430545  ...  80.430545             80.430545
+    11  1664.0  63.372618  ...  63.372618             62.929456
+    12  1792.0  72.983276  ...  63.142831             63.142831
     13  1920.0  69.120002  ...  71.626943             70.892307
-    14  2048.0  73.262953  ...  78.398206             78.033565
-    15  2176.0  83.155572  ...  87.494120             86.739860
-    16  2304.0  68.446623  ...  77.810656             77.558029
-    17  2432.0  71.305746  ...  75.726318             75.522751
-    18  2560.0  77.833728  ...  81.512437             81.715711
-    19  2688.0  83.552988  ...  90.966561             90.532356
-    20  2816.0  83.873477  ...  83.712490             83.712490
-    21  2944.0  81.832567  ...  84.040530             83.899046
-    22  3072.0  81.121923  ...  88.890270             88.750943
-    23  3200.0  84.544253  ...  95.665176             94.117647
-    24  3328.0  79.901550  ...  83.226931             84.795401
-    25  3456.0  82.519518  ...  88.692595             91.304157
-    26  3584.0  87.211821  ...  99.134944             99.684470
-    27  3712.0  80.757757  ...  86.790606             87.399253
-    28  3840.0  81.019778  ...  85.531326             91.322872
-    29  3968.0  86.114283  ...  90.522206             85.811488
-    30  4096.0  91.491294  ...  83.158446             85.816960
+    14  2048.0  73.584279  ...  78.398206             78.033565
+    15  2176.0  83.155572  ...  87.115360             86.739860
+    16  2304.0  68.251065  ...  77.810656             77.558029
+    17  2432.0  71.125224  ...  75.726318             75.320281
+    18  2560.0  77.833728  ...  81.920002             81.512437
+    19  2688.0  83.369354  ...  91.404957             90.748936
+    20  2816.0  83.392363  ...  83.712490             83.873477
+    21  2944.0  81.967162  ...  83.477440             82.373605
+    22  3072.0  78.752578  ...  88.612060             87.246694
+    23  3200.0  79.601989  ...  96.096095             95.952022
+    24  3328.0  84.003845  ...  85.196803             85.703924
+    25  3456.0  81.683457  ...  92.350019             92.508971
+    26  3584.0  84.745889  ...  88.412386             94.250936
+    27  3712.0  85.675250  ...  87.706180             87.399253
+    28  3840.0  83.465663  ...  88.332269             91.777595
+    29  3968.0  88.040360  ...  91.678389             86.788006
+    30  4096.0  93.531519  ...  83.156833             86.593830
 
     [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  58.307 seconds)
+   **Total running time of the script:** ( 6 minutes  8.669 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.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  356.173905   99.497980  315.076934
-    1    1536.0  405.098894  134.050910  344.523365
+    0    1024.0  361.411758   99.902435  315.076934
+    1    1536.0  409.599994  134.050910  344.523365
     2    2048.0  491.520012  159.067963  334.367350
-    3    2560.0  458.507457  182.314537  330.322572
+    3    2560.0  458.507457  182.857144  330.322572
     4    3072.0  522.893629  191.501303  321.956335
     5    3584.0  554.941930  207.768111  309.410081
-    6    4096.0  564.965515  220.907859  300.623865
-    7    4608.0  500.416301  232.336141  287.251954
-    8    5120.0  529.655159  243.809526  286.433562
+    6    4096.0  564.965515  220.907859  299.707322
+    7    4608.0  502.690905  232.336141  287.251954
+    8    5120.0  529.655159  243.809526  287.102804
     9    5632.0  542.843364  244.426754  291.939522
-    10   6144.0  550.208948  251.202731  288.000001
+    10   6144.0  552.269672  251.202731  288.000001
     11   6656.0  532.479975  255.590406  286.793541
-    12   7168.0  510.480705  253.734520  277.919225
-    13   7680.0  487.619051  266.358392  284.884090
-    14   8192.0  468.114289  258.354805  278.481578
+    12   7168.0  512.000004  253.734520  277.919225
+    13   7680.0  487.619051  266.743841  284.444450
+    14   8192.0  468.114289  258.694729  278.481578
     15   8704.0  414.476194  267.815384  285.377055
     16   9216.0  429.483477  272.394084  290.267724
-    17   9728.0  438.857162  279.942444  288.950501
+    17   9728.0  438.033784  280.278512  288.950501
     18  10240.0  444.412281  287.102804  290.153487
-    19  10752.0  427.231788  246.935876  289.941565
-    20  11264.0  427.071098  245.536784  286.069848
-    21  11776.0  418.702211  249.447482  288.686414
-    22  12288.0  415.369018  254.673582  294.323369
-    23  12800.0  410.695192  254.094291  289.811310
-    24  13312.0  410.125805  252.360194  289.391298
-    25  13824.0  404.604870  257.190689  291.799461
-    26  14336.0  396.387109  256.000002  289.129416
-    27  14848.0  385.662341  257.479779  288.777966
-    28  15360.0  379.259256  258.332158  287.550706
-    29  15872.0  372.000001  261.626369  290.562936
+    19  10752.0  426.525614  246.699797  289.941565
+    20  11264.0  427.071098  245.536784  286.372873
+    21  11776.0  418.702211  249.667843  288.981596
+    22  12288.0  415.369018  254.893699  294.323369
+    23  12800.0  410.695192  254.094291  289.538159
+    24  13312.0  409.599999  252.559690  289.391298
+    25  13824.0  404.112047  257.190689  292.056329
+    26  14336.0  396.387109  256.190622  288.886653
+    27  14848.0  385.662341  257.665934  288.777966
+    28  15360.0  378.869469  258.513318  287.775181
+    29  15872.0  372.000001  261.626369  290.341468
 
 
 
@@ -339,7 +339,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  12.274 seconds)
+   **Total running time of the script:** ( 2 minutes  13.855 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
 =================
-**13:16.634** total execution time for **getting-started_tutorials** files:
+**13:39.434** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:58.307 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:08.669 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:25.444 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:28.316 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:12.274 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:13.855 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:40.596 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:48.582 | 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 |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

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

@@ -324,7 +324,7 @@ for different problem sizes.</p>
            size      Triton       Torch
 0        4096.0    9.600000    9.600000
 1        8192.0   19.200000   19.200000
-2       16384.0   31.999999   38.400001
+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
@@ -340,7 +340,7 @@ for different problem sizes.</p>
 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  40.596 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  48.582 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

@@ -369,16 +369,16 @@ 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  512.000001      546.133347   190.511628
+0     256.0  546.133347      546.133347   188.321838
 1     384.0  585.142862      585.142862   151.703707
 2     512.0  655.360017      585.142849   156.038096
-3     640.0  682.666684      640.000002   160.000000
-4     768.0  722.823517      646.736871   163.839992
+3     640.0  682.666684      640.000002   158.759699
+4     768.0  722.823517      646.736871   162.754967
 ..      ...         ...             ...          ...
-93  12160.0  814.058574      405.755985   198.936606
-94  12288.0  815.800825      415.442160   199.197579
-95  12416.0  814.163950      412.149375   198.854847
-96  12544.0  814.214963      412.971190   199.012395
+93  12160.0  814.058574      406.179533   198.834951
+94  12288.0  814.111783      415.661740   199.096718
+95  12416.0  814.163950      412.149375   198.755369
+96  12544.0  814.214963      412.971190   198.913776
 97  12672.0  814.265046      412.097543   199.167004
 
 [98 rows x 4 columns]
@@ -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  25.444 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  28.316 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   2.730667  ...   3.276800              2.978909
-1    384.0   7.372800  ...   7.899428              7.899428
+1    384.0   7.372800  ...   8.507077              8.507077
 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  37.971025  ...  40.140799             40.140799
+5    896.0  37.971025  ...  41.321411             40.140799
 6   1024.0  49.932191  ...  53.773130             53.773130
 7   1152.0  44.566925  ...  48.161033             47.396572
 8   1280.0  51.200001  ...  57.690139             57.690139
 9   1408.0  64.138541  ...  69.009825             69.009825
-10  1536.0  80.430545  ...  81.355034             80.430545
-11  1664.0  62.929456  ...  63.372618             62.929456
-12  1792.0  72.983276  ...  63.142831             62.790080
+10  1536.0  80.430545  ...  80.430545             80.430545
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+12  1792.0  72.983276  ...  63.142831             63.142831
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-14  2048.0  73.262953  ...  78.398206             78.033565
-15  2176.0  83.155572  ...  87.494120             86.739860
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-17  2432.0  71.305746  ...  75.726318             75.522751
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-19  2688.0  83.552988  ...  90.966561             90.532356
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-23  3200.0  84.544253  ...  95.665176             94.117647
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-25  3456.0  82.519518  ...  88.692595             91.304157
-26  3584.0  87.211821  ...  99.134944             99.684470
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-28  3840.0  81.019778  ...  85.531326             91.322872
-29  3968.0  86.114283  ...  90.522206             85.811488
-30  4096.0  91.491294  ...  83.158446             85.816960
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+15  2176.0  83.155572  ...  87.115360             86.739860
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+24  3328.0  84.003845  ...  85.196803             85.703924
+25  3456.0  81.683457  ...  92.350019             92.508971
+26  3584.0  84.745889  ...  88.412386             94.250936
+27  3712.0  85.675250  ...  87.706180             87.399253
+28  3840.0  83.465663  ...  88.332269             91.777595
+29  3968.0  88.040360  ...  91.678389             86.788006
+30  4096.0  93.531519  ...  83.156833             86.593830
 
 [31 rows x 5 columns]
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