[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: 129fe056d957bceb5eb7005a87aa6582
+config: 5d1e5336b0fe1254665c1a22d9c46408
 tags: 645f666f9bcd5a90fca523b33c5a78b7

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

@@ -232,16 +232,16 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
 
     vector-add-performance:
                size      Triton       Torch
-    0        4096.0    8.000000    9.600000
+    0        4096.0    9.600000    9.600000
     1        8192.0   19.200000   19.200000
     2       16384.0   38.400001   38.400001
-    3       32768.0   76.800002   76.800002
+    3       32768.0   63.999998   63.999998
     4       65536.0  127.999995  127.999995
     5      131072.0  219.428568  219.428568
     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  46.935 seconds)
+   **Total running time of the script:** ( 1 minutes  24.953 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
+    0     256.0  512.000001      546.133347   190.511628
     1     384.0  585.142862      558.545450   151.703707
     2     512.0  655.360017      606.814814   154.566038
     3     640.0  682.666684      640.000002   158.759699
     4     768.0  722.823517      664.216187   163.839992
     ..      ...         ...             ...          ...
-    93  12160.0  814.058574      405.755985   198.733401
-    94  12288.0  814.111783      415.661740   198.995960
-    95  12416.0  814.163950      411.722274   198.705656
-    96  12544.0  814.214963      412.971190   198.815254
-    97  12672.0  814.265046      411.679167   198.971549
+    93  12160.0  814.058574      405.755985   198.530610
+    94  12288.0  814.111783      415.222812   198.794749
+    95  12416.0  814.163950      412.149375   198.457532
+    96  12544.0  814.214963      412.971190   198.618504
+    97  12672.0  814.265046      411.679167   198.776477
 
     [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  27.513 seconds)
+   **Total running time of the script:** ( 3 minutes  19.032 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
+    0    256.0   2.730667  ...    2.978909              3.276800
     1    384.0   7.372800  ...    7.899428              7.899428
-    2    512.0  14.563555  ...  15.420235             15.420235
+    2    512.0  14.563555  ...   15.420235             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
-    6   1024.0  49.932191  ...  53.773130             52.428801
+    5    896.0  37.971025  ...   40.140799             40.140799
+    6   1024.0  49.932191  ...   53.773130             53.773130
     7   1152.0  45.242181  ...   48.161033             47.396572
     8   1280.0  51.200001  ...   57.690139             57.690139
     9   1408.0  64.138541  ...   69.009825             68.147202
     10  1536.0  80.430545  ...   80.430545             80.430545
-    11  1664.0  63.372618  ...  63.372618             63.372618
+    11  1664.0  62.929456  ...   63.372618             62.929456
     12  1792.0  72.983276  ...   63.499573             63.142831
-    13  1920.0  69.120002  ...  71.626943             70.892307
-    14  2048.0  73.262953  ...  78.033565             77.672296
-    15  2176.0  83.155572  ...  87.115360             86.739860
-    16  2304.0  68.251065  ...  78.064941             77.558029
+    13  1920.0  68.776119  ...   71.257735             71.257735
+    14  2048.0  73.584279  ...   78.398206             78.033565
+    15  2176.0  83.500614  ...   87.115360             86.739860
+    16  2304.0  68.251065  ...   78.320893             77.810656
     17  2432.0  71.305746  ...   75.726318             75.522751
-    18  2560.0  77.833728  ...  82.125311             82.125311
-    19  2688.0  83.552988  ...  90.316801             90.966561
-    20  2816.0  83.233226  ...  83.233226             84.278666
-    21  2944.0  81.166173  ...  83.617504             84.182483
-    22  3072.0  81.825298  ...  89.451983             89.451983
-    23  3200.0  83.989503  ...  96.530922             94.256261
-    24  3328.0  83.905938  ...  86.946008             86.217120
-    25  3456.0  80.300370  ...  92.350019             88.497878
-    26  3584.0  87.381330  ...  98.053863             99.463928
-    27  3712.0  85.528545  ...  87.629253             88.326564
-    28  3840.0  82.716526  ...  88.971840             91.625518
-    29  3968.0  87.004591  ...  92.652949             85.841672
-    30  4096.0  93.727466  ...  89.092421             87.495257
+    18  2560.0  77.833728  ...   82.331658             81.715711
+    19  2688.0  83.552988  ...   90.966561             90.966561
+    20  2816.0  82.602666  ...   84.687779             84.523664
+    21  2944.0  82.921853  ...   83.758038             84.182483
+    22  3072.0  82.181572  ...   89.170242             88.197981
+    23  3200.0  81.321474  ...   95.238096             94.395283
+    24  3328.0  82.939284  ...   86.320498             85.908470
+    25  3456.0  80.140726  ...   87.727494             91.407671
+    26  3584.0  87.381330  ...  100.128496             99.684470
+    27  3712.0  83.247783  ...   87.629253             89.194055
+    28  3840.0  84.228485  ...   92.236860             85.533390
+    29  3968.0  91.885495  ...   85.093402             90.589410
+    30  4096.0  91.616198  ...   93.792965             91.242506
 
     [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  7.255 seconds)
+   **Total running time of the script:** ( 5 minutes  44.529 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  0.014 seconds)
+   **Total running time of the script:** ( 0 minutes  0.013 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:

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

@@ -39,35 +39,35 @@ Layer Normalization
     layer-norm-backward:
               N      Triton       Torch        Apex
     0    1024.0  361.411758   97.912354  303.407414
-    1    1536.0  405.098894  134.540150  341.333333
+    1    1536.0  409.599994  134.540150  341.333333
     2    2048.0  491.520012  161.154101  334.367350
-    3    2560.0  465.454542  181.238943  330.322572
+    3    2560.0  461.954908  181.238943  330.322572
     4    3072.0  519.211251  192.501302  323.368415
     5    3584.0  558.545477  208.271186  311.652167
-    6    4096.0  564.965515  220.907859  298.796351
+    6    4096.0  568.231237  220.907859  298.796351
     7    4608.0  502.690905  232.825259  287.251954
     8    5120.0  527.381977  242.366855  284.444444
     9    5632.0  542.843364  243.107920  289.438969
     10   6144.0  546.133354  248.661056  286.322318
     11   6656.0  527.207907  256.000009  285.767438
     12   7168.0  503.017523  259.867079  284.821192
-    13   7680.0  482.513091  263.314295  280.121579
-    14   8192.0  463.698115  266.767970  284.526763
+    13   7680.0  483.779539  262.938666  280.121579
+    14   8192.0  463.698115  266.587109  284.526763
     15   8704.0  414.476194  267.815384  284.599455
-    16   9216.0  427.822068  271.724806  287.999990
-    17   9728.0  437.213490  280.615388  290.027323
-    18  10240.0  446.836366  286.433562  290.496460
-    19  10752.0  429.364408  246.935876  290.267711
-    20  11264.0  426.397479  245.313973  286.980888
-    21  11776.0  420.571432  249.667843  288.981596
-    22  12288.0  416.542386  254.673582  294.323369
-    23  12800.0  411.244989  253.779426  289.811310
+    16   9216.0  426.996150  271.391419  287.999990
+    17   9728.0  437.213490  280.278512  290.027323
+    18  10240.0  446.025405  286.433562  290.496460
+    19  10752.0  429.364408  247.172406  290.594591
+    20  11264.0  427.071098  245.313973  286.980888
+    21  11776.0  421.198220  249.667843  289.277383
+    22  12288.0  416.542386  254.893699  294.617366
+    23  12800.0  411.244989  253.884294  289.811310
     24  13312.0  409.075539  252.959629  290.443638
     25  13824.0  405.098897  257.390218  292.056329
-    26  14336.0  395.021816  255.051144  286.719986
-    27  14848.0  386.080180  257.852379  289.481735
-    28  15360.0  380.433442  257.970599  286.879376
-    29  15872.0  371.094003  261.626369  289.679087
+    26  14336.0  395.021816  254.862216  287.198654
+    27  14848.0  386.498925  257.852379  289.717061
+    28  15360.0  380.433442  257.970599  287.550706
+    29  15872.0  370.552519  261.626369  290.120338
 
 
 
@@ -339,7 +339,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  14.074 seconds)
+   **Total running time of the script:** ( 2 minutes  12.505 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
 =================
-**13:35.790** total execution time for **getting-started_tutorials** files:
+**12:41.032** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:07.255 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:44.529 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:27.513 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:19.032 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:14.074 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 02:12.505 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:46.935 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:24.953 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.014 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.013 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

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

@@ -322,16 +322,16 @@ for different problem sizes.</p>
 <p class="sphx-glr-script-out">Out:</p>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>vector-add-performance:
            size      Triton       Torch
-0        4096.0    8.000000    9.600000
+0        4096.0    9.600000    9.600000
 1        8192.0   19.200000   19.200000
 2       16384.0   38.400001   38.400001
-3       32768.0   76.800002   76.800002
+3       32768.0   63.999998   63.999998
 4       65536.0  127.999995  127.999995
 5      131072.0  219.428568  219.428568
 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
@@ -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  46.935 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  24.953 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
+0     256.0  512.000001      546.133347   190.511628
 1     384.0  585.142862      558.545450   151.703707
 2     512.0  655.360017      606.814814   154.566038
 3     640.0  682.666684      640.000002   158.759699
 4     768.0  722.823517      664.216187   163.839992
 ..      ...         ...             ...          ...
-93  12160.0  814.058574      405.755985   198.733401
-94  12288.0  814.111783      415.661740   198.995960
-95  12416.0  814.163950      411.722274   198.705656
-96  12544.0  814.214963      412.971190   198.815254
-97  12672.0  814.265046      411.679167   198.971549
+93  12160.0  814.058574      405.755985   198.530610
+94  12288.0  814.111783      415.222812   198.794749
+95  12416.0  814.163950      412.149375   198.457532
+96  12544.0  814.214963      412.971190   198.618504
+97  12672.0  814.265046      411.679167   198.776477
 
 [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  27.513 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  19.032 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
+0    256.0   2.730667  ...    2.978909              3.276800
 1    384.0   7.372800  ...    7.899428              7.899428
-2    512.0  14.563555  ...  15.420235             15.420235
+2    512.0  14.563555  ...   15.420235             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
-6   1024.0  49.932191  ...  53.773130             52.428801
+5    896.0  37.971025  ...   40.140799             40.140799
+6   1024.0  49.932191  ...   53.773130             53.773130
 7   1152.0  45.242181  ...   48.161033             47.396572
 8   1280.0  51.200001  ...   57.690139             57.690139
 9   1408.0  64.138541  ...   69.009825             68.147202
 10  1536.0  80.430545  ...   80.430545             80.430545
-11  1664.0  63.372618  ...  63.372618             63.372618
+11  1664.0  62.929456  ...   63.372618             62.929456
 12  1792.0  72.983276  ...   63.499573             63.142831
-13  1920.0  69.120002  ...  71.626943             70.892307
-14  2048.0  73.262953  ...  78.033565             77.672296
-15  2176.0  83.155572  ...  87.115360             86.739860
-16  2304.0  68.251065  ...  78.064941             77.558029
+13  1920.0  68.776119  ...   71.257735             71.257735
+14  2048.0  73.584279  ...   78.398206             78.033565
+15  2176.0  83.500614  ...   87.115360             86.739860
+16  2304.0  68.251065  ...   78.320893             77.810656
 17  2432.0  71.305746  ...   75.726318             75.522751
-18  2560.0  77.833728  ...  82.125311             82.125311
-19  2688.0  83.552988  ...  90.316801             90.966561
-20  2816.0  83.233226  ...  83.233226             84.278666
-21  2944.0  81.166173  ...  83.617504             84.182483
-22  3072.0  81.825298  ...  89.451983             89.451983
-23  3200.0  83.989503  ...  96.530922             94.256261
-24  3328.0  83.905938  ...  86.946008             86.217120
-25  3456.0  80.300370  ...  92.350019             88.497878
-26  3584.0  87.381330  ...  98.053863             99.463928
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