[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: c8a6bdf06c7d292a5b258b2deb3c528d
+config: b7b18d2918a6a7e59cc1dc27cf229d11
 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   76.800002
+    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
@@ -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  45.824 seconds)
+   **Total running time of the script:** ( 1 minutes  37.620 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  512.000001      546.133347   188.321838
-    1     384.0  585.142862      558.545450   153.600004
+    0     256.0  512.000001      546.133347   192.752942
+    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      405.333344   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   198.913776
-    97  12672.0  814.265046      412.097543   199.069228
+    93  12160.0  814.058574      406.179533   199.038365
+    94  12288.0  814.111783      415.661740   199.298541
+    95  12416.0  814.163950      412.149375   198.854847
+    96  12544.0  814.214963      412.971190   199.111113
+    97  12672.0  814.265046      411.679167   199.167004
 
     [98 rows x 4 columns]
 
@@ -306,7 +306,7 @@ In the above plot, we can see that:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 3 minutes  21.745 seconds)
+   **Total running time of the script:** ( 3 minutes  18.443 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:

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

@@ -458,37 +458,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
 
     matmul-performance:
              M     cuBLAS  ...     Triton  Triton (+ LeakyReLU)
-    0    256.0   2.730667  ...   2.978909              2.978909
-    1    384.0   7.372800  ...   7.899428              8.507077
-    2    512.0  14.563555  ...  16.384000             15.420235
+    0    256.0   2.978909  ...   2.978909              2.978909
+    1    384.0   7.372800  ...   8.507077              8.507077
+    2    512.0  14.563555  ...  16.384000             16.384000
     3    640.0  22.260869  ...  24.380953             24.380953
     4    768.0  32.768000  ...  34.028308             34.028308
-    5    896.0  39.025776  ...  40.140799             37.971025
+    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
+    9   1408.0  64.138541  ...  67.305878             65.684049
     10  1536.0  80.430545  ...  79.526831             78.643199
-    11  1664.0  62.929456  ...  62.061463             62.492442
-    12  1792.0  72.512412  ...  71.588687             72.047592
-    13  1920.0  69.467336  ...  70.172588             70.172588
+    11  1664.0  62.929456  ...  62.492442             62.061463
+    12  1792.0  72.512412  ...  72.047592             72.047592
+    13  1920.0  69.120002  ...  70.172588             70.172588
     14  2048.0  73.262953  ...  76.608294             76.260072
-    15  2176.0  83.155572  ...  85.998493             85.998493
-    16  2304.0  68.643310  ...  76.809875             76.809875
-    17  2432.0  71.487187  ...  74.521127             84.877538
-    18  2560.0  77.833728  ...  81.108913             80.808877
-    19  2688.0  82.823267  ...  89.676257             89.464755
-    20  2816.0  80.617762  ...  82.602666             83.392363
-    21  2944.0  81.832567  ...  82.102191             82.102191
-    22  3072.0  82.121977  ...  88.335577             86.911900
-    23  3200.0  78.717759  ...  91.559367             92.753621
-    24  3328.0  79.990330  ...  83.130825             83.905938
-    25  3456.0  81.724858  ...  91.304157             90.892410
-    26  3584.0  83.101104  ...  91.563533             96.579370
-    27  3712.0  85.748791  ...  86.045381             91.901879
-    28  3840.0  80.313725  ...  86.265212             91.322872
-    29  3968.0  86.911637  ...  90.221021             83.922926
-    30  4096.0  92.755862  ...  88.301134             82.342167
+    15  2176.0  83.155572  ...  85.998493             85.269692
+    16  2304.0  68.446623  ...  77.057651             76.809875
+    17  2432.0  71.487187  ...  84.367759             85.134737
+    18  2560.0  78.019048  ...  80.908642             80.511054
+    19  2688.0  83.737433  ...  89.888756             89.254248
+    20  2816.0  81.827785  ...  82.602666             82.135981
+    21  2944.0  82.237674  ...  82.237674             82.102191
+    22  3072.0  81.589488  ...  88.473602             88.197981
+    23  3200.0  84.656085  ...  95.096582             94.955488
+    24  3328.0  83.034941  ...  84.200347             83.808259
+    25  3456.0  78.655188  ...  87.823058             87.632137
+    26  3584.0  87.466332  ...  98.375705             93.467144
+    27  3712.0  84.159518  ...  87.018592             88.092894
+    28  3840.0  79.505392  ...  87.217666             91.473945
+    29  3968.0  85.871877  ...  91.062642             84.038524
+    30  4096.0  93.012976  ...  86.396995             89.958266
 
     [31 rows x 5 columns]
 
@@ -498,7 +498,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 6 minutes  5.749 seconds)
+   **Total running time of the script:** ( 5 minutes  56.421 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  0.493 seconds)
+   **Total running time of the script:** ( 0 minutes  0.486 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
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-    1    1536.0  347.773587  135.529409  344.523365
-    2    2048.0  420.102553  162.217818  325.509933
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-    5    3584.0  547.872604  207.768111  311.652167
-    6    4096.0  564.965515  220.907859  301.546004
-    7    4608.0  504.986315  232.825259  288.751954
-    8    5120.0  531.948056  242.845844  285.104413
-    9    5632.0  545.032265  243.107920  290.060087
-    10   6144.0  548.163546  250.349744  286.879370
-    11   6656.0  537.858601  254.775119  285.767438
-    12   7168.0  508.970395  256.000002  279.726817
-    13   7680.0  485.052616  263.690977  278.009056
-    14   8192.0  462.607053  264.258058  280.068380
-    15   8704.0  417.791980  263.757583  282.291896
-    16   9216.0  430.319054  270.727053  286.879380
-    17   9728.0  440.513191  281.291575  290.027323
-    18  10240.0  449.287041  285.767451  289.129408
-    19  10752.0  429.364408  246.699797  289.941565
-    20  11264.0  424.389312  245.536784  287.591490
-    21  11776.0  421.198220  249.888595  288.686414
-    22  12288.0  417.722367  253.796902  294.617366
-    23  12800.0  415.135142  253.674644  289.811310
-    24  13312.0  409.599999  251.962147  289.129403
-    25  13824.0  404.604870  257.190689  292.056329
-    26  14336.0  395.930964  253.734520  287.438588
-    27  14848.0  384.829370  255.999999  288.544136
-    28  15360.0  376.932517  259.422943  289.583654
-    29  15872.0  367.336555  262.708969  290.784741
+    0    1024.0  311.088617   98.303995  307.200008
+    1    1536.0  347.773587  134.540150  344.523365
+    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  311.652167
+    6    4096.0  568.231237  220.412561  297.890900
+    7    4608.0  507.302750  232.825259  287.251954
+    8    5120.0  529.655159  242.845844  285.104413
+    9    5632.0  545.032265  243.545956  290.060087
+    10   6144.0  546.133354  248.661056  286.879370
+    11   6656.0  534.260858  256.000009  285.767438
+    12   7168.0  505.976473  260.654538  286.242939
+    13   7680.0  482.513091  262.564106  278.429013
+    14   8192.0  463.698115  267.493874  284.939124
+    15   8704.0  418.629245  267.815384  284.987724
+    16   9216.0  432.845409  272.394084  288.751954
+    17   9728.0  439.683593  280.615388  289.667485
+    18  10240.0  448.467168  286.433562  290.153487
+    19  10752.0  426.525614  247.172406  290.922209
+    20  11264.0  427.071098  245.536784  286.676558
+    21  11776.0  423.724129  249.667843  288.981596
+    22  12288.0  419.504980  254.673582  294.323369
+    23  12800.0  413.458944  253.465340  289.811310
+    24  13312.0  412.242569  252.959629  290.048115
+    25  13824.0  405.594132  257.190689  292.056329
+    26  14336.0  395.021816  254.485198  286.719986
+    27  14848.0  386.498925  257.665934  289.246765
+    28  15360.0  373.495460  257.970599  288.000007
+    29  15872.0  371.274849  261.806182  289.899545
 
 
 
@@ -339,7 +339,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  12.916 seconds)
+   **Total running time of the script:** ( 2 minutes  11.775 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
 =================
-**13:26.728** total execution time for **getting-started_tutorials** files:
+**13:04.745** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:05.749 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:56.421 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:21.745 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:18.443 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:12.916 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:11.775 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:45.824 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:37.620 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.493 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.486 | 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   76.800002
+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
@@ -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  45.824 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  37.620 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  512.000001      546.133347   188.321838
-1     384.0  585.142862      558.545450   153.600004
+0     256.0  512.000001      546.133347   192.752942
+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      405.333344   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   198.913776
-97  12672.0  814.265046      412.097543   199.069228
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+95  12416.0  814.163950      412.149375   198.854847
+96  12544.0  814.214963      412.971190   199.111113
+97  12672.0  814.265046      411.679167   199.167004
 
 [98 rows x 4 columns]
 </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  21.745 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  18.443 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

@@ -564,42 +564,42 @@ 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   2.730667  ...   2.978909              2.978909
-1    384.0   7.372800  ...   7.899428              8.507077
-2    512.0  14.563555  ...  16.384000             15.420235
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+1    384.0   7.372800  ...   8.507077              8.507077
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 4    768.0  32.768000  ...  34.028308             34.028308
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 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
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 10  1536.0  80.430545  ...  79.526831             78.643199
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-12  1792.0  72.512412  ...  71.588687             72.047592
-13  1920.0  69.467336  ...  70.172588             70.172588
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