diff --git a/_downloads/662999063954282841dc90b8945f85ce/tutorials_jupyter.zip b/_downloads/662999063954282841dc90b8945f85ce/tutorials_jupyter.zip
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diff --git a/_downloads/763344228ae6bc253ed1a6cf586aa30d/tutorials_python.zip b/_downloads/763344228ae6bc253ed1a6cf586aa30d/tutorials_python.zip
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diff --git a/_images/sphx_glr_01-vector-add_001.png b/_images/sphx_glr_01-vector-add_001.png
index d67565252..c0f205c2e 100644
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diff --git a/_images/sphx_glr_01-vector-add_thumb.png b/_images/sphx_glr_01-vector-add_thumb.png
index c5777d89d..a834079aa 100644
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diff --git a/_images/sphx_glr_02-fused-softmax_001.png b/_images/sphx_glr_02-fused-softmax_001.png
index bfd5a2661..721ec8718 100644
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diff --git a/_images/sphx_glr_02-fused-softmax_thumb.png b/_images/sphx_glr_02-fused-softmax_thumb.png
index 5d504ffcb..d80c266d9 100644
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diff --git a/_images/sphx_glr_03-matrix-multiplication_001.png b/_images/sphx_glr_03-matrix-multiplication_001.png
index 9e4a025bf..0c5355637 100644
Binary files a/_images/sphx_glr_03-matrix-multiplication_001.png and b/_images/sphx_glr_03-matrix-multiplication_001.png differ
diff --git a/_images/sphx_glr_03-matrix-multiplication_thumb.png b/_images/sphx_glr_03-matrix-multiplication_thumb.png
index ed55bbfd1..80a31e691 100644
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diff --git a/_sources/getting-started/tutorials/01-vector-add.rst.txt b/_sources/getting-started/tutorials/01-vector-add.rst.txt
index 4b5349fd7..c7608afeb 100644
--- a/_sources/getting-started/tutorials/01-vector-add.rst.txt
+++ b/_sources/getting-started/tutorials/01-vector-add.rst.txt
@@ -219,10 +219,10 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
     0        4096.0    9.540372    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  384.000001  384.000001
+    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
@@ -230,7 +230,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
     11    8388608.0  812.429770  812.429770
     12   16777216.0  833.084721  833.084721
     13   33554432.0  843.811163  843.811163
-    14   67108864.0  849.278610  848.362445
+    14   67108864.0  848.362445  848.362445
     15  134217728.0  851.577704  850.656574
 
 
@@ -239,7 +239,7 @@ 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:** ( 0 minutes  11.115 seconds)
+   **Total running time of the script:** ( 0 minutes  10.987 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
diff --git a/_sources/getting-started/tutorials/02-fused-softmax.rst.txt b/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
index 0d7d657f5..dd6668edf 100644
--- a/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
+++ b/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
@@ -262,15 +262,15 @@ 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   273.066674
-    1     384.0  585.142862      585.142862   267.130429
-    2     512.0  630.153853      606.814814   264.258068
+    1     384.0  585.142862      585.142862   261.446801
+    2     512.0  655.360017      585.142849   264.258068
     3     640.0  682.666684      640.000002   269.473696
     4     768.0  702.171410      664.216187   273.066663
     ..      ...         ...             ...          ...
-    93  12160.0  812.359066      405.755985   329.483481
+    93  12160.0  812.359066      406.179533   329.204728
     94  12288.0  812.429770      415.222812   329.602681
-    95  12416.0  810.840807      412.149375   329.173158
-    96  12544.0  810.925276      412.971190   329.292871
+    95  12416.0  810.840807      412.149375   328.900662
+    96  12544.0  810.925276      412.546756   329.292871
     97  12672.0  811.007961      412.097543   329.142870
 
     [98 rows x 4 columns]
@@ -290,7 +290,7 @@ In the above plot, we can see that:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  8.181 seconds)
+   **Total running time of the script:** ( 1 minutes  8.170 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
diff --git a/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt b/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
index 31405d45f..f8f05a4ac 100644
--- a/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
+++ b/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
@@ -371,37 +371,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
     matmul-performance:
              M     cuBLAS  ...     Triton  Triton (+ LeakyReLU)
     0    128.0   0.455111  ...   0.512000              0.512000
-    1    256.0   2.730667  ...   2.978909              2.978909
+    1    256.0   2.730667  ...   3.276800              2.978909
     2    384.0   7.372800  ...   8.507077              8.507077
     3    512.0  14.563555  ...  16.384000             15.420235
     4    640.0  22.260869  ...  24.380953             24.380953
     5    768.0  32.768000  ...  34.028308             34.028308
     6    896.0  37.971025  ...  39.025776             37.971025
-    7   1024.0  51.150050  ...  52.428801             52.428801
-    8   1152.0  45.242181  ...  46.656000             46.656000
+    7   1024.0  49.932191  ...  52.428801             52.428801
+    8   1152.0  44.566925  ...  46.656000             45.938215
     9   1280.0  51.200001  ...  56.109587             56.109587
-    10  1408.0  64.138541  ...  65.684049             58.621246
-    11  1536.0  79.526831  ...  76.106321             75.296679
+    10  1408.0  64.138541  ...  65.684049             65.684049
+    11  1536.0  80.430545  ...  76.106321             76.106321
     12  1664.0  63.372618  ...  61.636381             61.636381
-    13  1792.0  72.983276  ...  69.379162             68.953520
-    14  1920.0  69.467336  ...  68.435645             69.467336
-    15  2048.0  73.584279  ...  75.915006             75.234154
-    16  2176.0  80.817862  ...  78.608000             79.855747
-    17  2304.0  68.446623  ...  73.051599             72.607513
-    18  2432.0  71.125224  ...  80.499895             80.499895
-    19  2560.0  77.833728  ...  76.740048             76.027843
-    20  2688.0  82.823267  ...  80.027544             82.823267
-    21  2816.0  84.197315  ...  78.442822             76.785575
-    22  2944.0  81.698415  ...  79.356738             78.729910
-    23  3072.0  81.005868  ...  83.761985             81.707223
-    24  3200.0  84.432717  ...  88.642656             84.321474
-    25  3328.0  83.130825  ...  81.622783             80.980084
-    26  3456.0  80.864158  ...  84.864807             80.864158
-    27  3584.0  87.381330  ...  89.116127             84.988707
-    28  3712.0  84.230479  ...  85.091436             83.806497
-    29  3840.0  83.465663  ...  84.809814             86.265212
-    30  3968.0  92.793868  ...  84.797731             83.807647
-    31  4096.0  93.466385  ...  91.553703             91.180520
+    13  1792.0  72.983276  ...  68.533074             68.533074
+    14  1920.0  68.098521  ...  70.172588             70.172588
+    15  2048.0  73.908442  ...  75.234154             75.573044
+    16  2176.0  83.155572  ...  80.173899             79.855747
+    17  2304.0  68.251065  ...  73.051599             72.828879
+    18  2432.0  71.125224  ...  81.433227             81.433227
+    19  2560.0  77.833728  ...  76.920185             75.676673
+    20  2688.0  83.552988  ...  80.880718             82.823267
+    21  2816.0  82.446516  ...  78.868366             79.733474
+    22  2944.0  82.373605  ...  80.251257             79.610276
+    23  3072.0  77.993256  ...  81.943708             83.514905
+    24  3200.0  84.210524  ...  89.887639             84.544253
+    25  3328.0  83.130825  ...  81.346098             82.088138
+    26  3456.0  80.140726  ...  82.943999             81.600781
+    27  3584.0  87.296493  ...  95.451583             96.269155
+    28  3712.0  84.301560  ...  89.194055             89.035062
+    29  3840.0  85.267542  ...  83.718392             84.292684
+    30  3968.0  89.921841  ...  87.035620             86.664727
+    31  4096.0  92.820009  ...  91.366730             91.741443
 
     [32 rows x 5 columns]
 
@@ -411,7 +411,7 @@ 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:** ( 2 minutes  17.256 seconds)
+   **Total running time of the script:** ( 2 minutes  5.849 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
diff --git a/_sources/getting-started/tutorials/sg_execution_times.rst.txt b/_sources/getting-started/tutorials/sg_execution_times.rst.txt
index 217f816e3..2fb9c48c7 100644
--- a/_sources/getting-started/tutorials/sg_execution_times.rst.txt
+++ b/_sources/getting-started/tutorials/sg_execution_times.rst.txt
@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**03:36.552** total execution time for **getting-started_tutorials** files:
+**03:25.006** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:17.256 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:05.849 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 01:08.181 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 01:08.170 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 00:11.115 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 00:10.987 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/getting-started/tutorials/01-vector-add.html b/getting-started/tutorials/01-vector-add.html
index b7428bd6c..8ce87a43e 100644
--- a/getting-started/tutorials/01-vector-add.html
+++ b/getting-started/tutorials/01-vector-add.html
@@ -308,10 +308,10 @@ for different problem sizes.</p>
 0        4096.0    9.540372    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  384.000001  384.000001
+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
@@ -319,11 +319,11 @@ for different problem sizes.</p>
 11    8388608.0  812.429770  812.429770
 12   16777216.0  833.084721  833.084721
 13   33554432.0  843.811163  843.811163
-14   67108864.0  849.278610  848.362445
+14   67108864.0  848.362445  848.362445
 15  134217728.0  851.577704  850.656574
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  11.115 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  10.987 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>
diff --git a/getting-started/tutorials/02-fused-softmax.html b/getting-started/tutorials/02-fused-softmax.html
index 4d0b54612..dbe394f8c 100644
--- a/getting-started/tutorials/02-fused-softmax.html
+++ b/getting-started/tutorials/02-fused-softmax.html
@@ -347,15 +347,15 @@ 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  512.000001      546.133347   273.066674
-1     384.0  585.142862      585.142862   267.130429
-2     512.0  630.153853      606.814814   264.258068
+1     384.0  585.142862      585.142862   261.446801
+2     512.0  655.360017      585.142849   264.258068
 3     640.0  682.666684      640.000002   269.473696
 4     768.0  702.171410      664.216187   273.066663
 ..      ...         ...             ...          ...
-93  12160.0  812.359066      405.755985   329.483481
+93  12160.0  812.359066      406.179533   329.204728
 94  12288.0  812.429770      415.222812   329.602681
-95  12416.0  810.840807      412.149375   329.173158
-96  12544.0  810.925276      412.971190   329.292871
+95  12416.0  810.840807      412.149375   328.900662
+96  12544.0  810.925276      412.546756   329.292871
 97  12672.0  811.007961      412.097543   329.142870
 
 [98 rows x 4 columns]
@@ -370,7 +370,7 @@ This means that – when temporary data is too large to fit entirely in the GPU
 Note that our Triton kernel is not only faster than PyTorch’s CUDA kernel, it is also <strong>easier to read, understand and maintain</strong>.</p></li>
 </ul>
 </div></blockquote>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  8.181 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  8.170 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>
diff --git a/getting-started/tutorials/03-matrix-multiplication.html b/getting-started/tutorials/03-matrix-multiplication.html
index d35067395..6c2de53f2 100644
--- a/getting-started/tutorials/03-matrix-multiplication.html
+++ b/getting-started/tutorials/03-matrix-multiplication.html
@@ -476,42 +476,42 @@ tensor(True, device=&#39;cuda:0&#39;)
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
          M     cuBLAS  ...     Triton  Triton (+ LeakyReLU)
 0    128.0   0.455111  ...   0.512000              0.512000
-1    256.0   2.730667  ...   2.978909              2.978909
+1    256.0   2.730667  ...   3.276800              2.978909
 2    384.0   7.372800  ...   8.507077              8.507077
 3    512.0  14.563555  ...  16.384000             15.420235
 4    640.0  22.260869  ...  24.380953             24.380953
 5    768.0  32.768000  ...  34.028308             34.028308
 6    896.0  37.971025  ...  39.025776             37.971025
-7   1024.0  51.150050  ...  52.428801             52.428801
-8   1152.0  45.242181  ...  46.656000             46.656000
+7   1024.0  49.932191  ...  52.428801             52.428801
+8   1152.0  44.566925  ...  46.656000             45.938215
 9   1280.0  51.200001  ...  56.109587             56.109587
-10  1408.0  64.138541  ...  65.684049             58.621246
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-22  2944.0  81.698415  ...  79.356738             78.729910
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-26  3456.0  80.864158  ...  84.864807             80.864158
-27  3584.0  87.381330  ...  89.116127             84.988707
-28  3712.0  84.230479  ...  85.091436             83.806497
-29  3840.0  83.465663  ...  84.809814             86.265212
-30  3968.0  92.793868  ...  84.797731             83.807647
-31  4096.0  93.466385  ...  91.553703             91.180520
+13  1792.0  72.983276  ...  68.533074             68.533074
+14  1920.0  68.098521  ...  70.172588             70.172588
+15  2048.0  73.908442  ...  75.234154             75.573044
+16  2176.0  83.155572  ...  80.173899             79.855747
+17  2304.0  68.251065  ...  73.051599             72.828879
+18  2432.0  71.125224  ...  81.433227             81.433227
+19  2560.0  77.833728  ...  76.920185             75.676673
+20  2688.0  83.552988  ...  80.880718             82.823267
+21  2816.0  82.446516  ...  78.868366             79.733474
+22  2944.0  82.373605  ...  80.251257             79.610276
+23  3072.0  77.993256  ...  81.943708             83.514905
+24  3200.0  84.210524  ...  89.887639             84.544253
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