[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: cf684901b57e59ede0e9a6458a97c96b
+config: 41a8f7ded8f17e74cdc1cd298d4905e1
 tags: 645f666f9bcd5a90fca523b33c5a78b7

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

@@ -238,10 +238,10 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
     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  341.333321
+    6      262144.0  341.333321  384.000001
     7      524288.0  472.615390  472.615390
     8     1048576.0  614.400016  614.400016
-    9     2097152.0  722.823517  722.823517
+    9     2097152.0  722.823517  702.171410
     10    4194304.0  780.190482  780.190482
     11    8388608.0  812.429770  812.429770
     12   16777216.0  833.084721  833.084721
@@ -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  41.559 seconds)
+   **Total running time of the script:** ( 1 minutes  38.076 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      512.000001   186.181817
+    0     256.0  512.000001      546.133347   188.321838
     1     384.0  614.400016      585.142862   153.600004
-    2     512.0  655.360017      585.142849   154.566038
+    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  812.359066      406.179533   198.429370
-    94  12288.0  812.429770      415.661740   198.794749
-    95  12416.0  812.498981      412.149375   198.457532
-    96  12544.0  812.566838      412.546756   198.716830
-    97  12672.0  811.007961      412.097543   198.776477
+    93  12160.0  812.359066      406.179533   198.834951
+    94  12288.0  812.429770      415.222812   199.096718
+    95  12416.0  812.498981      412.149375   198.755369
+    96  12544.0  810.925276      412.971190   198.913776
+    97  12672.0  811.007961      411.888249   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  21.850 seconds)
+   **Total running time of the script:** ( 3 minutes  21.149 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:

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

@@ -459,12 +459,12 @@ 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              3.276800
-    1    384.0   7.372800  ...   7.899428              7.899428
-    2    512.0  14.563555  ...  15.420235             15.420235
+    0    256.0   2.730667  ...   3.276800              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  ...  35.389441             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  ...  53.773130             52.428801
     7   1152.0  45.242181  ...  48.161033             47.396572
     8   1280.0  51.200001  ...  57.690139             57.690139
@@ -472,24 +472,24 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
     10  1536.0  80.430545  ...  81.355034             78.643199
     11  1664.0  63.372618  ...  63.372618             62.492442
     12  1792.0  72.983276  ...  73.460287             59.467852
-    13  1920.0  69.467336  ...  71.257735             70.892307
-    14  2048.0  73.262953  ...  78.033565             76.959706
-    15  2176.0  83.155572  ...  87.494120             85.998493
-    16  2304.0  68.446623  ...  78.064941             77.057651
-    17  2432.0  71.125224  ...  86.444504             84.877538
-    18  2560.0  77.833728  ...  82.956960             81.108913
-    19  2688.0  83.552988  ...  90.966561             89.044730
-    20  2816.0  82.995641  ...  84.197315             83.712490
-    21  2944.0  82.646820  ...  83.758038             82.237674
-    22  3072.0  82.661468  ...  87.787755             88.612060
-    23  3200.0  81.424937  ...  93.704243             93.430660
-    24  3328.0  81.622783  ...  85.703924             84.795401
-    25  3456.0  82.604067  ...  92.033756             90.281712
-    26  3584.0  85.674507  ...  93.273228             95.960933
-    27  3712.0  85.748791  ...  86.118401             87.706180
-    28  3840.0  81.019778  ...  88.900318             89.475729
-    29  3968.0  88.008611  ...  87.315873             88.040360
-    30  4096.0  93.924229  ...  93.727466             87.552332
+    13  1920.0  68.776119  ...  71.626943             70.892307
+    14  2048.0  73.262953  ...  78.398206             76.959706
+    15  2176.0  83.155572  ...  87.876193             85.998493
+    16  2304.0  68.251065  ...  78.064941             77.057651
+    17  2432.0  71.305746  ...  86.711310             84.115159
+    18  2560.0  77.833728  ...  82.539044             81.512437
+    19  2688.0  83.737433  ...  90.966561             89.044730
+    20  2816.0  83.712490  ...  84.523664             83.712490
+    21  2944.0  82.784108  ...  83.060049             82.646820
+    22  3072.0  82.661468  ...  90.020831             87.787755
+    23  3200.0  85.219705  ...  96.822991             95.952022
+    24  3328.0  83.613586  ...  86.528001             84.200347
+    25  3456.0  81.849303  ...  91.928814             88.595129
+    26  3584.0  86.540320  ...  99.463928             91.563533
+    27  3712.0  82.355598  ...  89.154253             81.283434
+    28  3840.0  84.874902  ...  93.722032             85.399230
+    29  3968.0  93.469117  ...  89.198780             86.175099
+    30  4096.0  92.436452  ...  86.313653             82.241256
 
     [31 rows x 5 columns]
 
@@ -499,7 +499,7 @@ 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  59.034 seconds)
+   **Total running time of the script:** ( 6 minutes  2.032 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  0.469 seconds)
+   **Total running time of the script:** ( 0 minutes  0.474 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:

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

@@ -41,32 +41,32 @@ Layer Normalization
     0    1024.0  585.142849  277.694907  468.114273
     1    1536.0  630.153868  323.368435  511.999982
     2    2048.0  682.666643  334.367358  520.126988
-    3    2560.0  694.237267  362.477870  518.481028
-    4    3072.0  712.347810  378.092307  496.484863
-    5    3584.0  725.873439  384.859062  458.751978
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+    5    3584.0  725.873439  384.859062  451.527536
     6    4096.0  728.177767  381.023256  451.972420
-    7    4608.0  670.254540  396.387087  426.173427
-    8    5120.0  694.237267  397.669909  426.666652
-    9    5632.0  704.000002  395.228063  413.357796
+    7    4608.0  676.403666  396.387087  431.157877
+    8    5120.0  688.403381  397.669909  422.268057
+    9    5632.0  704.000002  395.228063  415.262685
     10   6144.0  702.171410  402.885254  411.313806
-    11   6656.0  700.631610  400.360920  398.861429
-    12   7168.0  690.891575  396.844306  387.459443
-    13   7680.0  682.666656  392.587863  387.634072
-    14   8192.0  639.375598  393.609605  371.308771
-    15   8704.0  630.153861  389.005597  380.502740
-    16   9216.0  609.322328  407.337026  383.999986
-    17   9728.0  589.575753  409.599987  383.369452
-    18  10240.0  566.920437  408.578556  382.803739
-    19  10752.0  549.623009  411.559798  381.445676
-    20  11264.0  536.380957  406.826188  373.134567
-    21  11776.0  523.377770  409.599991  377.587162
+    11   6656.0  700.631610  398.861429  400.360920
+    12   7168.0  686.754468  395.475867  386.154893
+    13   7680.0  682.666656  392.587863  386.415087
+    14   8192.0  642.509816  387.786968  368.179771
+    15   8704.0  630.153861  387.922008  378.434774
+    16   9216.0  609.322328  407.337026  383.002605
+    17   9728.0  589.575753  408.524944  383.369452
+    18  10240.0  566.920437  409.600010  382.803739
+    19  10752.0  549.623009  410.577576  381.445676
+    20  11264.0  534.789310  406.826188  374.686074
+    21  11776.0  523.377770  409.599991  376.831982
     22  12288.0  516.031509  413.911572  383.251457
-    23  12800.0  505.679014  410.420828  376.470582
-    24  13312.0  494.180982  405.699062  376.310952
-    25  13824.0  482.934503  411.888257  379.389355
-    26  14336.0  471.967074  406.695045  374.185964
-    27  14848.0  461.297068  408.192434  375.304904
-    28  15360.0  454.269882  406.214870  378.092307
+    23  12800.0  505.679014  409.599981  376.470582
+    24  13312.0  494.180982  405.699062  376.976995
+    25  13824.0  481.882350  412.656711  379.389355
+    26  14336.0  471.967074  405.975225  372.969090
+    27  14848.0  461.297068  406.794504  375.304904
+    28  15360.0  454.269882  406.887417  377.511515
     29  15872.0  447.887117  406.974373  376.225175
 
 
@@ -389,7 +389,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  20.722 seconds)
+   **Total running time of the script:** ( 5 minutes  22.534 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
 =================
-**16:23.634** total execution time for **getting-started_tutorials** files:
+**16:24.265** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:59.034 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:02.032 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:20.722 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:22.534 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:21.850 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:21.149 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:41.559 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:38.076 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.469 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.474 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

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

@@ -328,10 +328,10 @@ for different problem sizes.</p>
 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  341.333321
+6      262144.0  341.333321  384.000001
 7      524288.0  472.615390  472.615390
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-9     2097152.0  722.823517  722.823517
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 10    4194304.0  780.190482  780.190482
 11    8388608.0  812.429770  812.429770
 12   16777216.0  833.084721  833.084721
@@ -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  41.559 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  38.076 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      512.000001   186.181817
+0     256.0  512.000001      546.133347   188.321838
 1     384.0  614.400016      585.142862   153.600004
-2     512.0  655.360017      585.142849   154.566038
+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  812.359066      406.179533   198.429370
-94  12288.0  812.429770      415.661740   198.794749
-95  12416.0  812.498981      412.149375   198.457532
-96  12544.0  812.566838      412.546756   198.716830
-97  12672.0  811.007961      412.097543   198.776477
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+94  12288.0  812.429770      415.222812   199.096718
+95  12416.0  812.498981      412.149375   198.755369
+96  12544.0  810.925276      412.971190   198.913776
+97  12672.0  811.007961      411.888249   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  21.850 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  21.149 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

@@ -565,12 +565,12 @@ 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  ...   3.276800              3.276800
-1    384.0   7.372800  ...   7.899428              7.899428
-2    512.0  14.563555  ...  15.420235             15.420235
+0    256.0   2.730667  ...   3.276800              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  ...  35.389441             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  ...  53.773130             52.428801
 7   1152.0  45.242181  ...  48.161033             47.396572
 8   1280.0  51.200001  ...  57.690139             57.690139
@@ -578,29 +578,29 @@ torch_output=tensor([[  1.1045, -36.9688,  31.4688,  ..., -11.3906,  24.4531, -3
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-14  2048.0  73.262953  ...  78.033565             76.959706
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-25  3456.0  82.604067  ...  92.033756             90.281712
-26  3584.0  85.674507  ...  93.273228             95.960933
-27  3712.0  85.748791  ...  86.118401             87.706180
-28  3840.0  81.019778  ...  88.900318             89.475729
-29  3968.0  88.008611  ...  87.315873             88.040360
-30  4096.0  93.924229  ...  93.727466             87.552332
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