[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: d4d2f4c1324dbd398a6698be141f3883
+config: 3713c272a80f7b98e5b262b1104402b1
 tags: 645f666f9bcd5a90fca523b33c5a78b7

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

@@ -234,11 +234,11 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
                size      Triton       Torch
     0        4096.0    9.600000    9.600000
     1        8192.0   19.200000   19.200000
-    2       16384.0   38.400001   38.400001
+    2       16384.0   31.999999   38.400001
     3       32768.0   76.800002   76.800002
     4       65536.0  127.999995  127.999995
     5      131072.0  219.428568  219.428568
-    6      262144.0  384.000001  384.000001
+    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  722.823517
@@ -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  37.083 seconds)
+   **Total running time of the script:** ( 1 minutes  47.685 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      546.133347   195.047621
+    0     256.0  512.000001      512.000001   188.321838
     1     384.0  614.400016      585.142862   153.600004
     2     512.0  655.360017      585.142849   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   199.038365
-    94  12288.0  812.429770      416.101597   199.298541
-    95  12416.0  812.498981      412.149375   198.954424
-    96  12544.0  810.925276      412.546756   199.209928
-    97  12672.0  811.007961      412.097543   199.264875
+    93  12160.0  812.359066      406.179533   198.530610
+    94  12288.0  812.429770      415.661740   198.895304
+    95  12416.0  812.498981      412.149375   198.457532
+    96  12544.0  810.925276      412.971190   198.716830
+    97  12672.0  811.007961      412.097543   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  32.694 seconds)
+   **Total running time of the script:** ( 3 minutes  33.159 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              3.276800
-    1    384.0   7.372800  ...   7.899428              8.507077
-    2    512.0  14.563555  ...  15.420235             16.384000
+    0    256.0   2.730667  ...   2.978909              2.978909
+    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  39.025776  ...  40.140799             39.025776
-    6   1024.0  51.150050  ...  53.773130             52.428801
+    5    896.0  37.971025  ...  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
     9   1408.0  64.138541  ...  68.147202             67.305878
-    10  1536.0  80.430545  ...  81.355034             79.526831
+    10  1536.0  79.526831  ...  81.355034             79.526831
     11  1664.0  63.372618  ...  63.372618             62.492442
-    12  1792.0  72.983276  ...  73.460287             59.467852
+    12  1792.0  72.983276  ...  72.983276             59.467852
     13  1920.0  69.120002  ...  71.257735             70.892307
-    14  2048.0  73.908442  ...  78.398206             77.314362
-    15  2176.0  83.155572  ...  88.261612             86.367588
-    16  2304.0  68.446623  ...  78.064941             77.558029
-    17  2432.0  71.305746  ...  86.711310             85.915795
-    18  2560.0  78.019048  ...  82.539044             81.310171
-    19  2688.0  83.552988  ...  90.102270             89.888756
-    20  2816.0  83.712490  ...  84.852542             83.873477
-    21  2944.0  82.373605  ...  83.758038             82.921853
-    22  3072.0  82.540970  ...  85.922766             88.335577
-    23  3200.0  84.993363  ...  96.676741             96.385543
-    24  3328.0  84.003845  ...  86.217120             81.162679
-    25  3456.0  81.026701  ...  85.767626             89.183149
-    26  3584.0  87.211821  ...  99.463928             97.840469
-    27  3712.0  83.247783  ...  89.273764             84.088676
-    28  3840.0  85.070769  ...  90.723546             88.686451
-    29  3968.0  93.219206  ...  88.103928             87.441013
-    30  4096.0  90.565269  ...  86.037005             82.597115
+    14  2048.0  73.584279  ...  78.398206             77.314362
+    15  2176.0  83.155572  ...  87.494120             85.632545
+    16  2304.0  68.446623  ...  78.064941             77.307030
+    17  2432.0  71.305746  ...  86.711310             86.179335
+    18  2560.0  78.019048  ...  82.331658             81.715711
+    19  2688.0  83.369354  ...  90.532356             89.464755
+    20  2816.0  84.360174  ...  84.687779             83.873477
+    21  2944.0  82.373605  ...  83.758038             82.102191
+    22  3072.0  82.540970  ...  89.593522             88.612060
+    23  3200.0  84.544253  ...  96.822991             95.665176
+    24  3328.0  83.905938  ...  85.398926             84.101981
+    25  3456.0  82.773682  ...  86.318594             88.400840
+    26  3584.0  86.457107  ...  97.416461             98.699661
+    27  3712.0  83.317214  ...  88.955779             85.491947
+    28  3840.0  84.036474  ...  93.801526             84.679936
+    29  3968.0  93.576636  ...  81.025193             81.512316
+    30  4096.0  88.475759  ...  93.858555             89.928129
 
     [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  17.371 seconds)
+   **Total running time of the script:** ( 7 minutes  24.521 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  0.280 seconds)
+   **Total running time of the script:** ( 0 minutes  0.282 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:

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

@@ -42,14 +42,14 @@ Layer Normalization
     1    1536.0  630.153868  323.368435  511.999982
     2    2048.0  668.734716  334.367358  520.126988
     3    2560.0  694.237267  362.477870  512.000013
-    4    3072.0  712.347810  378.092307  501.551037
+    4    3072.0  712.347810  375.206126  496.484863
     5    3584.0  725.873439  384.859062  455.111115
-    6    4096.0  728.177767  381.023256  458.293714
-    7    4608.0  670.254540  396.387087  431.157877
-    8    5120.0  688.403381  397.669909  422.268057
-    9    5632.0  704.000002  396.969169  417.185184
-    10   6144.0  697.191505  402.885254  411.313806
-    11   6656.0  705.271522  400.360920  400.360920
+    6    4096.0  728.177767  381.023256  448.876695
+    7    4608.0  670.254540  396.387087  426.173427
+    8    5120.0  688.403381  397.669909  426.666652
+    9    5632.0  698.542675  396.969169  413.357796
+    10   6144.0  702.171410  402.885254  411.313806
+    11   6656.0  700.631610  400.360920  400.360920
     12   7168.0  690.891575  396.844306  387.459443
     13   7680.0  678.895043  393.846167  387.634072
     14   8192.0  633.198054  393.609605  371.308771
@@ -59,9 +59,9 @@ Layer Normalization
     18  10240.0  564.965524  408.578556  382.803739
     19  10752.0  547.872604  411.559798  381.445676
     20  11264.0  533.207081  406.826188  373.134567
-    21  11776.0  520.486200  410.492372  378.345375
+    21  11776.0  520.486200  409.599991  378.345375
     22  12288.0  514.680630  414.784810  383.251457
-    23  12800.0  504.433489  410.420828  377.163903
+    23  12800.0  504.433489  410.420828  376.470582
     24  13312.0  494.180982  405.699062  376.976995
     25  13824.0  481.882350  411.888257  379.389355
     26  14336.0  471.967074  406.695045  374.185964
@@ -393,7 +393,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  38.079 seconds)
+   **Total running time of the script:** ( 5 minutes  40.195 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:

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

@@ -385,7 +385,7 @@ This is a Triton implementation of the Flash Attention algorithm
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  0.073 seconds)
+   **Total running time of the script:** ( 0 minutes  0.072 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  0.264 seconds)
+   **Total running time of the script:** ( 0 minutes  0.253 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
 =================
-**18:05.845** total execution time for **getting-started_tutorials** files:
+**18:26.166** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 07:17.371 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 07:24.521 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:38.079 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:40.195 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:32.694 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:33.159 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:37.083 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:47.685 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.280 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.282 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_07-libdevice-function.py` (``07-libdevice-function.py``)       | 00:00.264 | 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_06-fused-attention.py` (``06-fused-attention.py``)             | 00:00.073 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_06-fused-attention.py` (``06-fused-attention.py``)             | 00:00.072 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

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

@@ -326,11 +326,11 @@ for different problem sizes.</p>
            size      Triton       Torch
 0        4096.0    9.600000    9.600000
 1        8192.0   19.200000   19.200000
-2       16384.0   38.400001   38.400001
+2       16384.0   31.999999   38.400001
 3       32768.0   76.800002   76.800002
 4       65536.0  127.999995  127.999995
 5      131072.0  219.428568  219.428568
-6      262144.0  384.000001  384.000001
+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  722.823517
@@ -342,7 +342,7 @@ 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  37.083 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  47.685 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

@@ -371,17 +371,17 @@ 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      546.133347   195.047621
+0     256.0  512.000001      512.000001   188.321838
 1     384.0  614.400016      585.142862   153.600004
 2     512.0  655.360017      585.142849   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   199.038365
-94  12288.0  812.429770      416.101597   199.298541
-95  12416.0  812.498981      412.149375   198.954424
-96  12544.0  810.925276      412.546756   199.209928
-97  12672.0  811.007961      412.097543   199.264875
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+94  12288.0  812.429770      415.661740   198.895304
+95  12416.0  812.498981      412.149375   198.457532
+96  12544.0  810.925276      412.971190   198.716830
+97  12672.0  811.007961      412.097543   198.776477
 
 [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  32.694 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  33.159 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              3.276800
-1    384.0   7.372800  ...   7.899428              8.507077
-2    512.0  14.563555  ...  15.420235             16.384000
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+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  39.025776  ...  40.140799             39.025776
-6   1024.0  51.150050  ...  53.773130             52.428801
+5    896.0  37.971025  ...  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
 9   1408.0  64.138541  ...  68.147202             67.305878
-10  1536.0  80.430545  ...  81.355034             79.526831
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 11  1664.0  63.372618  ...  63.372618             62.492442
-12  1792.0  72.983276  ...  73.460287             59.467852
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 13  1920.0  69.120002  ...  71.257735             70.892307
-14  2048.0  73.908442  ...  78.398206             77.314362
-15  2176.0  83.155572  ...  88.261612             86.367588
-16  2304.0  68.446623  ...  78.064941             77.558029
-17  2432.0  71.305746  ...  86.711310             85.915795
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-24  3328.0  84.003845  ...  86.217120             81.162679
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-26  3584.0  87.211821  ...  99.463928             97.840469
-27  3712.0  83.247783  ...  89.273764             84.088676
-28  3840.0  85.070769  ...  90.723546             88.686451
-29  3968.0  93.219206  ...  88.103928             87.441013
-30  4096.0  90.565269  ...  86.037005             82.597115
+14  2048.0  73.584279  ...  78.398206             77.314362
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