[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: ca77bb6474c45e6f0da200b497be637e
+config: dcb51d10379790b23b9f305eb4789868
 tags: 645f666f9bcd5a90fca523b33c5a78b7

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

@@ -241,13 +241,13 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
     6      262144.0  341.333321  341.333321
     7      524288.0  472.615390  472.615390
     8     1048576.0  614.400016  614.400016
-    9     2097152.0  722.823517  702.171410
+    9     2097152.0  702.171410  702.171410
-    10    4194304.0  780.190482  780.190482
+    10    4194304.0  780.190482  768.000002
     11    8388608.0  812.429770  812.429770
     12   16777216.0  833.084721  833.084721
     13   33554432.0  842.004273  842.004273
     14   67108864.0  847.448255  848.362445
-    15  134217728.0  850.196756  850.656574
+    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  52.088 seconds)
+   **Total running time of the script:** ( 1 minutes  48.554 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   190.511628
+    0     256.0  512.000001      546.133347   186.181817
-    1     384.0  585.142862      558.545450   149.853661
+    1     384.0  438.857137      558.545450   151.703707
-    2     512.0  655.360017      585.142849   154.566038
+    2     512.0  468.114273      585.142849   154.566038
-    3     640.0  682.666684      640.000002   158.759699
+    3     640.0  465.454542      640.000002   158.759699
-    4     768.0  722.823517      646.736871   162.754967
+    4     768.0  472.615390      664.216187   163.839992
     ..      ...         ...             ...          ...
-    93  12160.0  815.765209      405.755985   198.631953
+    93  12160.0  478.034381      405.333344   198.834951
-    94  12288.0  814.111783      416.101597   198.794749
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-    95  12416.0  815.835709      412.149375   198.457532
+    95  12416.0  461.454135      411.296057   198.755369
-    96  12544.0  814.214963      412.971190   198.618504
+    96  12544.0  458.228323      412.971190   198.815254
-    97  12672.0  814.265046      412.097543   198.776477
+    97  12672.0  458.196617      411.679167   198.971549
 
     [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  32.198 seconds)
+   **Total running time of the script:** ( 3 minutes  10.849 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  ...   2.978909              2.978909
-    1    384.0   7.372800  ...   7.899428              8.507077
+    1    384.0   7.372800  ...   8.507077              8.507077
-    2    512.0  14.563555  ...  15.420235             16.384000
+    2    512.0  14.563555  ...  15.420235             15.420235
     3    640.0  22.260869  ...  24.380953             24.380953
-    4    768.0  31.597714  ...  34.028308             34.028308
+    4    768.0  32.768000  ...  34.028308             34.028308
-    5    896.0  36.971791  ...  40.140799             39.025776
+    5    896.0  37.971025  ...  40.140799             40.140799
-    6   1024.0  48.770977  ...  52.428801             52.428801
+    6   1024.0  49.932191  ...  53.773130             52.428801
-    7   1152.0  43.911529  ...  46.656000             46.656000
+    7   1152.0  45.242181  ...  48.161033             47.396572
-    8   1280.0  49.951220  ...  56.888887             56.109587
+    8   1280.0  51.200001  ...  57.690139             57.690139
-    9   1408.0  62.664092  ...  67.305878             66.485074
+    9   1408.0  64.138541  ...  68.147202             67.305878
-    10  1536.0  78.643199  ...  78.643199             77.778988
+    10  1536.0  79.526831  ...  79.526831             79.526831
-    11  1664.0  61.636381  ...  62.061463             61.636381
+    11  1664.0  62.929456  ...  62.929456             62.492442
-    12  1792.0  71.588687  ...  67.707374             67.707374
+    12  1792.0  72.512412  ...  63.142831             62.790080
-    13  1920.0  67.764707  ...  70.172588             69.818184
+    13  1920.0  69.120002  ...  71.626943             70.892307
-    14  2048.0  72.005219  ...  76.608294             76.260072
+    14  2048.0  73.584279  ...  78.033565             77.672296
-    15  2176.0  81.803444  ...  85.632545             85.269692
+    15  2176.0  83.155572  ...  87.115360             86.739860
-    16  2304.0  67.100763  ...  76.563695             76.319081
+    16  2304.0  68.251065  ...  78.064941             77.558029
-    17  2432.0  69.886725  ...  74.323979             73.932798
+    17  2432.0  71.125224  ...  75.522751             75.320281
-    18  2560.0  76.382283  ...  80.908642             80.511054
+    18  2560.0  77.833728  ...  82.331658             81.920002
-    19  2688.0  82.642823  ...  89.676257             89.254248
+    19  2688.0  83.645109  ...  90.102270             90.102270
-    20  2816.0  82.602666  ...  82.916747             82.759409
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-    21  2944.0  81.166173  ...  82.509987             82.169877
+    21  2944.0  82.509987  ...  82.852924             82.646820
-    22  3072.0  81.005868  ...  88.197981             88.060814
+    22  3072.0  82.540970  ...  86.845249             89.593522
-    23  3200.0  83.660130  ...  95.522391             95.096582
+    23  3200.0  84.993363  ...  96.240602             96.096095
-    24  3328.0  82.369902  ...  84.795401             84.596116
+    24  3328.0  83.034941  ...  83.905938             82.843841
-    25  3456.0  81.026701  ...  91.304157             90.994998
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-    26  3584.0  86.374055  ...  98.699661             98.375705
+    26  3584.0  85.797134  ...  93.467144             98.483450
-    27  3712.0  84.874549  ...  88.876645             88.483034
+    27  3712.0  85.748791  ...  86.754095             88.170647
-    28  3840.0  84.036474  ...  92.545605             92.159996
+    28  3840.0  81.798814  ...  87.841141             91.473945
-    29  3968.0  92.232760  ...  91.062642             91.403695
+    29  3968.0  85.871877  ...  92.582651             84.738843
-    30  4096.0  93.206754  ...  93.012976             92.820009
+    30  4096.0  94.386588  ...  84.894196             82.722796
 
     [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  41.514 seconds)
+   **Total running time of the script:** ( 6 minutes  44.900 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  0.411 seconds)
+   **Total running time of the script:** ( 0 minutes  0.325 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  356.173905   96.755900  299.707322
+    0    1024.0  114.306981   98.698793  315.076934
-    1    1536.0  400.695643  133.083026  338.201833
+    1    1536.0  118.153850  132.604320  341.333333
-    2    2048.0  486.653476  159.584422  321.254900
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-    3    2560.0  455.111129  179.649115  323.368411
+    3    2560.0  119.300966  180.705883  332.108113
-    4    3072.0  508.468972  191.005181  320.556515
+    4    3072.0  123.912607  191.005181  320.556515
-    5    3584.0  551.384634  206.769233  310.527060
+    5    3584.0  127.809806  207.267476  310.527060
-    6    4096.0  558.545450  219.919464  297.890900
+    6    4096.0  130.723400  220.907859  296.990947
-    7    4608.0  493.714279  231.364016  285.767436
+    7    4608.0  105.325718  232.336141  287.999990
-    8    5120.0  518.481012  241.414550  283.133649
+    8    5120.0  108.647215  241.414550  283.787523
-    9    5632.0  534.260858  241.803217  288.820505
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-    10   6144.0  540.131844  247.409397  285.214712
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-    11   6656.0  525.473708  255.182111  284.748652
+    11   6656.0  112.733948  254.775119  285.257135
-    12   7168.0  503.017523  259.084340  283.881181
+    12   7168.0  114.994654  257.147993  281.098038
-    13   7680.0  482.513091  262.190612  275.104486
+    13   7680.0  115.128047  264.068761  281.834874
-    14   8192.0  463.698115  265.686491  283.296835
+    14   8192.0  115.856217  267.493874  282.889211
-    15   8704.0  406.412440  266.789264  283.826081
+    15   8704.0   94.054934  264.091015  282.673891
-    16   9216.0  419.703988  270.727053  287.251954
+    16   9216.0   96.755908  271.391419  287.625496
-    17   9728.0  428.388977  279.942444  288.950501
+    17   9728.0   97.768843  280.615388  288.950501
-    18  10240.0  437.295395  285.104413  286.767793
+    18  10240.0  100.105904  285.104413  289.129408
-    19  10752.0  424.421071  245.292781  289.291486
+    19  10752.0  101.036809  246.464170  290.594591
-    20  11264.0  423.724120  244.426754  286.069848
+    20  11264.0  102.945926  245.536784  286.676558
-    21  11776.0  418.702211  247.915800  288.097854
+    21  11776.0  103.601171  249.447482  288.981596
-    22  12288.0  414.784810  253.578674  293.737063
+    22  12288.0  106.159829  254.673582  294.911986
-    23  12800.0  409.327110  252.631590  287.371378
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-    24  13312.0  408.030638  252.360194  289.653667
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-    25  13824.0  403.620451  256.197690  291.287079
+    25  13824.0  107.544896  256.792581  292.313649
-    26  14336.0  394.116833  253.921779  286.242939
+    26  14336.0  109.435116  254.673567  287.198654
-    27  14848.0  384.829370  257.108233  289.246765
+    27  14848.0  109.276912  255.266469  289.481735
-    28  15360.0  380.041240  257.071134  284.884090
+    28  15360.0  110.669469  260.338991  290.496454
-    29  15872.0  370.913333  260.731015  289.679087
+    29  15872.0  110.863792  263.071829  291.898841
 
 
 
@@ -339,7 +339,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  16.519 seconds)
+   **Total running time of the script:** ( 2 minutes  2.489 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
 =================
-**14:22.730** total execution time for **getting-started_tutorials** files:
+**13:47.116** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:41.514 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:44.900 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:32.198 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:10.849 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:16.519 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:02.489 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:52.088 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:48.554 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.411 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.325 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

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

@@ -331,16 +331,16 @@ for different problem sizes.</p>
 6      262144.0  341.333321  341.333321
 7      524288.0  472.615390  472.615390
 8     1048576.0  614.400016  614.400016
-9     2097152.0  722.823517  702.171410
+9     2097152.0  702.171410  702.171410
-10    4194304.0  780.190482  780.190482
+10    4194304.0  780.190482  768.000002
 11    8388608.0  812.429770  812.429770
 12   16777216.0  833.084721  833.084721
 13   33554432.0  842.004273  842.004273
 14   67108864.0  847.448255  848.362445
-15  134217728.0  850.196756  850.656574
+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  52.088 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  48.554 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   190.511628
+0     256.0  512.000001      546.133347   186.181817
-1     384.0  585.142862      558.545450   149.853661
+1     384.0  438.857137      558.545450   151.703707
-2     512.0  655.360017      585.142849   154.566038
+2     512.0  468.114273      585.142849   154.566038
-3     640.0  682.666684      640.000002   158.759699
+3     640.0  465.454542      640.000002   158.759699
-4     768.0  722.823517      646.736871   162.754967
+4     768.0  472.615390      664.216187   163.839992
 ..      ...         ...             ...          ...
-93  12160.0  815.765209      405.755985   198.631953
+93  12160.0  478.034381      405.333344   198.834951
-94  12288.0  814.111783      416.101597   198.794749
+94  12288.0  484.256150      415.222812   199.096718
-95  12416.0  815.835709      412.149375   198.457532
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-96  12544.0  814.214963      412.971190   198.618504
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-97  12672.0  814.265046      412.097543   198.776477
+97  12672.0  458.196617      411.679167   198.971549
 
 [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  32.198 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  10.849 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  ...   2.978909              2.978909
-1    384.0   7.372800  ...   7.899428              8.507077
+1    384.0   7.372800  ...   8.507077              8.507077
-2    512.0  14.563555  ...  15.420235             16.384000
+2    512.0  14.563555  ...  15.420235             15.420235
 3    640.0  22.260869  ...  24.380953             24.380953
-4    768.0  31.597714  ...  34.028308             34.028308
+4    768.0  32.768000  ...  34.028308             34.028308
-5    896.0  36.971791  ...  40.140799             39.025776
+5    896.0  37.971025  ...  40.140799             40.140799
-6   1024.0  48.770977  ...  52.428801             52.428801
+6   1024.0  49.932191  ...  53.773130             52.428801
-7   1152.0  43.911529  ...  46.656000             46.656000
+7   1152.0  45.242181  ...  48.161033             47.396572
-8   1280.0  49.951220  ...  56.888887             56.109587
+8   1280.0  51.200001  ...  57.690139             57.690139
-9   1408.0  62.664092  ...  67.305878             66.485074
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