[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: 5ab336a702bbdecaaa31e7a15d0c8cb1
+config: bbf13b0f91abba000f682ef71c0ca565
 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   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
@@ -245,7 +245,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
     10    4194304.0  780.190482  780.190482
     11    8388608.0  812.429770  812.429770
     12   16777216.0  833.084721  833.084721
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+    13   33554432.0  842.004273  843.811163
     14   67108864.0  847.448255  848.362445
     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  49.605 seconds)
+   **Total running time of the script:** ( 1 minutes  46.048 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:

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

@@ -279,16 +279,16 @@ 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  546.133347      546.133347   188.321838
-    1     384.0  614.400016      558.545450   151.703707
+    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   158.759699
-    4     768.0  722.823517      664.216187   163.839992
+    3     640.0  706.206879      640.000002   160.000000
+    4     768.0  722.823517      664.216187   162.754967
     ..      ...         ...             ...          ...
-    93  12160.0  812.359066      405.755985   198.733401
-    94  12288.0  812.429770      415.222812   198.995960
-    95  12416.0  812.498981      412.149375   198.655991
-    96  12544.0  810.925276      412.971190   198.815254
-    97  12672.0  811.007961      412.097543   198.971549
+    93  12160.0  812.359066      406.179533   198.936606
+    94  12288.0  812.429770      415.661740   199.197579
+    95  12416.0  812.498981      412.149375   198.854847
+    96  12544.0  810.925276      412.546756   199.111113
+    97  12672.0  811.007961      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  32.100 seconds)
+   **Total running time of the script:** ( 3 minutes  27.135 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:

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

@@ -459,37 +459,37 @@ 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  ...   8.507077              8.507077
+    0    256.0   2.978909  ...   2.978909              3.276800
+    1    384.0   7.372800  ...   7.899428              7.899428
     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             39.025776
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     6   1024.0  49.932191  ...  53.773130             52.428801
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     8   1280.0  51.200001  ...  57.690139             57.690139
-    9   1408.0  64.138541  ...  69.009825             67.305878
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     10  1536.0  80.430545  ...  81.355034             79.526831
     11  1664.0  62.929456  ...  63.372618             62.492442
     12  1792.0  72.512412  ...  73.460287             59.467852
-    13  1920.0  69.120002  ...  71.257735             71.257735
-    14  2048.0  73.584279  ...  78.033565             77.314362
-    15  2176.0  83.155572  ...  87.494120             85.998493
-    16  2304.0  68.251065  ...  78.064941             77.307030
-    17  2432.0  71.305746  ...  86.179335             75.118889
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+    14  2048.0  73.908442  ...  78.398206             77.314362
+    15  2176.0  83.155572  ...  87.876193             85.998493
+    16  2304.0  68.446623  ...  78.064941             77.057651
+    17  2432.0  71.305746  ...  84.367759             75.320281
     18  2560.0  77.833728  ...  82.747477             81.715711
-    19  2688.0  83.922689  ...  90.966561             88.836198
-    20  2816.0  79.733474  ...  83.873477             83.074685
-    21  2944.0  82.509987  ...  83.617504             82.373605
-    22  3072.0  81.530748  ...  89.735509             88.060814
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-    24  3328.0  82.843841  ...  85.754970             83.808259
-    25  3456.0  80.945348  ...  85.133652             81.271743
-    26  3584.0  87.466332  ...  95.249353             98.699661
-    27  3712.0  85.896254  ...  81.283434             87.706180
-    28  3840.0  81.019778  ...  86.332554             89.766237
-    29  3968.0  85.751184  ...  90.388098             86.114283
-    30  4096.0  91.867031  ...  83.081233             89.807782
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+    21  2944.0  82.509987  ...  83.337844             82.373605
+    22  3072.0  81.707223  ...  89.310890             89.030036
+    23  3200.0  84.656085  ...  96.530922             94.674553
+    24  3328.0  82.369902  ...  85.398926             85.096096
+    25  3456.0  82.099354  ...  91.824110             90.382926
+    26  3584.0  85.633710  ...  98.375705             98.591437
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+    30  4096.0  87.495257  ...  88.127204             91.242506
 
     [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:** ( 7 minutes  11.851 seconds)
+   **Total running time of the script:** ( 6 minutes  30.888 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  0.290 seconds)
+   **Total running time of the script:** ( 0 minutes  0.012 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:
               N      Triton       Torch        Apex
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+    0    1024.0  585.142849  277.694907  468.114273
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-    6    4096.0  728.177767  383.251446  451.972420
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+    5    3584.0  725.873439  384.859062  448.000001
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     8    5120.0  688.403381  397.669909  424.455959
-    9    5632.0  698.542675  398.725657  411.470331
-    10   6144.0  697.191505  404.543206  409.600010
-    11   6656.0  700.631610  400.360920  400.360920
-    12   7168.0  686.754468  383.571898  383.571898
-    13   7680.0  682.666656  392.587863  386.415087
-    14   8192.0  639.375598  392.431125  373.424507
-    15   8704.0  624.502255  391.191007  380.502740
-    16   9216.0  604.327881  403.989025  382.010363
-    17   9728.0  585.142883  409.599987  383.369452
-    18  10240.0  564.965524  409.600010  382.803739
-    19  10752.0  546.133312  410.577576  380.601764
-    20  11264.0  530.070590  396.969169  367.804077
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+    11   6656.0  700.631610  398.861429  400.360920
+    12   7168.0  690.891575  396.844306  387.459443
+    13   7680.0  678.895043  393.846167  386.415087
+    14   8192.0  636.271854  393.609605  371.308771
+    15   8704.0  627.315309  389.005597  380.502740
+    16   9216.0  606.814809  407.337026  383.999986
+    17   9728.0  587.350922  409.599987  383.369452
+    18  10240.0  564.965524  408.578556  381.911416
+    19  10752.0  546.133312  411.559798  381.445676
+    20  11264.0  533.207081  406.826188  373.134567
+    21  11776.0  520.486200  409.599991  377.587162
     22  12288.0  513.336807  413.911572  383.251457
-    23  12800.0  504.433489  410.420828  377.163903
-    24  13312.0  494.180982  408.030638  376.976995
-    25  13824.0  481.882350  412.656711  379.389355
-    26  14336.0  471.967074  398.914774  371.158581
-    27  14848.0  461.297068  406.794504  375.304904
-    28  15360.0  454.269882  406.887417  377.511515
-    29  15872.0  447.887117  408.282944  376.225175
+    23  12800.0  504.433489  410.420828  376.470582
+    24  13312.0  494.180982  405.699062  376.976995
+    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
+    29  15872.0  447.098578  406.974373  376.783377
 
 
 
@@ -393,7 +393,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  37.085 seconds)
+   **Total running time of the script:** ( 5 minutes  36.789 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:

master/_sources/getting-started/tutorials/06-fused-attention.rst.txt

@@ -390,7 +390,7 @@ This is a Triton implementation of the Flash Attention algorithm
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  0.072 seconds)
+   **Total running time of the script:** ( 0 minutes  0.071 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_06-fused-attention.py:

master/_sources/getting-started/tutorials/07-libdevice-function.rst.txt

@@ -152,7 +152,7 @@ We can also customize the libdevice library path by passing the path to the `lib
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  0.253 seconds)
+   **Total running time of the script:** ( 0 minutes  0.010 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_07-libdevice-function.py:

master/_sources/getting-started/tutorials/sg_execution_times.rst.txt

@@ -5,20 +5,20 @@
 
 Computation times
 =================
-**18:11.256** total execution time for **getting-started_tutorials** files:
+**17:20.953** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 07:11.851 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:30.888 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:37.085 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:36.789 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:32.100 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:27.135 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:49.605 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:46.048 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.290 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``)             | 00:00.071 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_07-libdevice-function.py` (``07-libdevice-function.py``)       | 00:00.253 | 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 |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``)             | 00:00.072 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_07-libdevice-function.py` (``07-libdevice-function.py``)       | 00:00.010 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

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

@@ -327,7 +327,7 @@ 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   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
@@ -337,12 +337,12 @@ for different problem sizes.</p>
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 11    8388608.0  812.429770  812.429770
 12   16777216.0  833.084721  833.084721
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+13   33554432.0  842.004273  843.811163
 14   67108864.0  847.448255  848.362445
 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  49.605 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  46.048 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

@@ -372,16 +372,16 @@ We will then compare its performance against (1) <code class="code docutils lite
 <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      546.133347   188.321838
-1     384.0  614.400016      558.545450   151.703707
+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   158.759699
-4     768.0  722.823517      664.216187   163.839992
+3     640.0  706.206879      640.000002   160.000000
+4     768.0  722.823517      664.216187   162.754967
 ..      ...         ...             ...          ...
-93  12160.0  812.359066      405.755985   198.733401
-94  12288.0  812.429770      415.222812   198.995960
-95  12416.0  812.498981      412.149375   198.655991
-96  12544.0  810.925276      412.971190   198.815254
-97  12672.0  811.007961      412.097543   198.971549
+93  12160.0  812.359066      406.179533   198.936606
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+95  12416.0  812.498981      412.149375   198.854847
+96  12544.0  810.925276      412.546756   199.111113
+97  12672.0  811.007961      412.097543   199.167004
 
 [98 rows x 4 columns]
 </pre></div>
@@ -394,7 +394,7 @@ 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  32.100 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  27.135 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

@@ -567,42 +567,42 @@ 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  ...   8.507077              8.507077
+0    256.0   2.978909  ...   2.978909              3.276800
+1    384.0   7.372800  ...   7.899428              7.899428
 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             39.025776
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master/getting-started/tutorials/04-low-memory-dropout.html

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