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 8d66f2ebe..21e64bc56 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 23a1a41d8..44bbedff7 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 492aabb50..c07120a38 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 f32bdca56..948084dca 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 332180243..f514168f3 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 840bf0b0a..57ebee22b 100644
Binary files a/_images/sphx_glr_03-matrix-multiplication_thumb.png and b/_images/sphx_glr_03-matrix-multiplication_thumb.png differ
diff --git a/_sources/getting-started/tutorials/01-vector-add.rst.txt b/_sources/getting-started/tutorials/01-vector-add.rst.txt
index 72865e81d..3d9232522 100644
--- a/_sources/getting-started/tutorials/01-vector-add.rst.txt
+++ b/_sources/getting-started/tutorials/01-vector-add.rst.txt
@@ -216,13 +216,13 @@ We can now run the decorated function above. Pass `show_plots=True` to see the p
 
     vector-add-performance:
                size      Triton       Torch
-    0        4096.0    9.540372    9.600000
+    0        4096.0    9.600000    9.600000
     1        8192.0   19.200000   19.200000
-    2       16384.0   31.999999   31.999999
-    3       32768.0   63.999998   76.800002
+    2       16384.0   38.400001   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  341.333321  384.000001
+    6      262144.0  384.000001  384.000001
     7      524288.0  472.615390  472.615390
     8     1048576.0  614.400016  614.400016
     9     2097152.0  722.823517  722.823517
@@ -239,7 +239,7 @@ We can now run the decorated function above. Pass `show_plots=True` to see the p
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  10.999 seconds)
+   **Total running time of the script:** ( 0 minutes  10.992 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 d0dd7e38e..bacef6d46 100644
--- a/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
+++ b/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
@@ -261,11 +261,11 @@ 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   264.258068
-    1     384.0  585.142862      585.142862   261.446801
+    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
-    3     640.0  682.666684      640.000002   265.974036
-    4     768.0  702.171410      664.216187   273.066663
+    3     640.0  682.666684      640.000002   269.473696
+    4     768.0  702.171410      664.216187   276.134828
     ..      ...         ...             ...          ...
     93  12160.0  812.359066      406.179533   329.483481
     94  12288.0  812.429770      415.661740   329.602681
@@ -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  8.183 seconds)
+   **Total running time of the script:** ( 1 minutes  8.189 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 fa1148c99..2c1006e21 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  ...   3.276800              2.978909
+    1    256.0   2.978909  ...   2.978909              2.978909
     2    384.0   7.372800  ...   8.507077              8.507077
-    3    512.0  14.563555  ...  15.420235             15.420235
+    3    512.0  14.563555  ...  16.384000             16.384000
     4    640.0  22.260869  ...  24.380953             24.380953
     5    768.0  32.768000  ...  34.028308             34.028308
-    6    896.0  39.025776  ...  39.025776             39.025776
+    6    896.0  39.025776  ...  39.025776             37.971025
     7   1024.0  49.932191  ...  52.428801             52.428801
-    8   1152.0  44.566925  ...  46.656000             45.938215
+    8   1152.0  44.566925  ...  46.656000             46.656000
     9   1280.0  51.200001  ...  56.109587             56.109587
-    10  1408.0  64.138541  ...  65.684049             58.601554
-    11  1536.0  79.526831  ...  76.106321             75.296679
-    12  1664.0  63.372618  ...  61.636381             61.636381
-    13  1792.0  72.983276  ...  68.953520             68.533074
-    14  1920.0  69.120002  ...  69.467336             69.467336
-    15  2048.0  73.584279  ...  75.573044             75.234154
-    16  2176.0  83.155572  ...  79.226957             80.494588
-    17  2304.0  68.446623  ...  72.387489             72.607513
-    18  2432.0  71.125224  ...  80.269900             80.963875
-    19  2560.0  77.649287  ...  76.920185             76.740048
-    20  2688.0  84.108772  ...  81.053536             83.004501
-    21  2816.0  79.879498  ...  78.868366             79.011245
-    22  2944.0  81.698415  ...  77.505492             79.865439
-    23  3072.0  80.202695  ...  83.886078             83.391907
-    24  3200.0  82.262212  ...  89.385477             87.074829
-    25  3328.0  83.226931  ...  86.946008             81.715431
-    26  3456.0  78.578525  ...  84.420490             84.068369
-    27  3584.0  87.296493  ...  90.276496             85.064084
-    28  3712.0  83.386762  ...  83.876864             84.515517
-    29  3840.0  85.005380  ...  87.701820             87.493673
-    30  3968.0  92.864488  ...  84.562670             83.807647
-    31  4096.0  93.596744  ...  83.626378             91.616198
+    10  1408.0  64.138541  ...  66.485074             65.684049
+    11  1536.0  80.430545  ...  76.106321             76.106321
+    12  1664.0  63.372618  ...  62.061463             60.803457
+    13  1792.0  72.512412  ...  68.953520             68.533074
+    14  1920.0  69.120002  ...  69.467336             68.776119
+    15  2048.0  73.584279  ...  75.915006             75.915006
+    16  2176.0  83.500614  ...  80.817862             80.494588
+    17  2304.0  68.446623  ...  72.828879             72.607513
+    18  2432.0  71.125224  ...  79.139336             79.813818
+    19  2560.0  77.833728  ...  76.740048             75.328737
+    20  2688.0  84.108772  ...  79.524227             83.369354
+    21  2816.0  82.135981  ...  78.868366             76.516158
+    22  2944.0  81.967162  ...  81.034195             79.737653
+    23  3072.0  81.825298  ...  83.146995             83.761985
+    24  3200.0  84.210524  ...  89.887639             86.137280
+    25  3328.0  82.464255  ...  82.843841             86.424125
+    26  3456.0  82.604067  ...  87.442050             82.435141
+    27  3584.0  86.540320  ...  96.683219             90.458141
+    28  3712.0  84.946722  ...  82.084920             87.170458
+    29  3840.0  84.421376  ...  86.806905             86.063813
+    30  3968.0  92.652949  ...  87.472354             87.284643
+    31  4096.0  93.401342  ...  91.553703             91.678778
 
     [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  13.184 seconds)
+   **Total running time of the script:** ( 2 minutes  14.506 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 837d794ca..8427dbe98 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
 =================
-**03:32.367** total execution time for **getting-started_tutorials** files:
+**03:33.687** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:13.184 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:14.506 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 01:08.183 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 01:08.189 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 00:10.999 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 00:10.992 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/getting-started/tutorials/01-vector-add.html b/getting-started/tutorials/01-vector-add.html
index 184bcb0ff..ca3211c19 100644
--- a/getting-started/tutorials/01-vector-add.html
+++ b/getting-started/tutorials/01-vector-add.html
@@ -305,13 +305,13 @@ 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    9.540372    9.600000
+0        4096.0    9.600000    9.600000
 1        8192.0   19.200000   19.200000
-2       16384.0   31.999999   31.999999
-3       32768.0   63.999998   76.800002
+2       16384.0   38.400001   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  341.333321  384.000001
+6      262144.0  384.000001  384.000001
 7      524288.0  472.615390  472.615390
 8     1048576.0  614.400016  614.400016
 9     2097152.0  722.823517  722.823517
@@ -323,7 +323,7 @@ for different problem sizes.</p>
 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  10.999 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  10.992 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 2a04c4f9e..4aa2643f8 100644
--- a/getting-started/tutorials/02-fused-softmax.html
+++ b/getting-started/tutorials/02-fused-softmax.html
@@ -346,11 +346,11 @@ 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   264.258068
-1     384.0  585.142862      585.142862   261.446801
+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
-3     640.0  682.666684      640.000002   265.974036
-4     768.0  702.171410      664.216187   273.066663
+3     640.0  682.666684      640.000002   269.473696
+4     768.0  702.171410      664.216187   276.134828
 ..      ...         ...             ...          ...
 93  12160.0  812.359066      406.179533   329.483481
 94  12288.0  812.429770      415.661740   329.602681
@@ -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  8.183 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  8.189 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 a8648a828..49eb43ac3 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  ...   3.276800              2.978909
+1    256.0   2.978909  ...   2.978909              2.978909
 2    384.0   7.372800  ...   8.507077              8.507077
-3    512.0  14.563555  ...  15.420235             15.420235
+3    512.0  14.563555  ...  16.384000             16.384000
 4    640.0  22.260869  ...  24.380953             24.380953
 5    768.0  32.768000  ...  34.028308             34.028308
-6    896.0  39.025776  ...  39.025776             39.025776
+6    896.0  39.025776  ...  39.025776             37.971025
 7   1024.0  49.932191  ...  52.428801             52.428801
-8   1152.0  44.566925  ...  46.656000             45.938215
+8   1152.0  44.566925  ...  46.656000             46.656000
 9   1280.0  51.200001  ...  56.109587             56.109587
-10  1408.0  64.138541  ...  65.684049             58.601554
-11  1536.0  79.526831  ...  76.106321             75.296679
-12  1664.0  63.372618  ...  61.636381             61.636381
-13  1792.0  72.983276  ...  68.953520             68.533074
-14  1920.0  69.120002  ...  69.467336             69.467336
-15  2048.0  73.584279  ...  75.573044             75.234154
-16  2176.0  83.155572  ...  79.226957             80.494588
-17  2304.0  68.446623  ...  72.387489             72.607513
-18  2432.0  71.125224  ...  80.269900             80.963875
-19  2560.0  77.649287  ...  76.920185             76.740048
-20  2688.0  84.108772  ...  81.053536             83.004501
-21  2816.0  79.879498  ...  78.868366             79.011245
-22  2944.0  81.698415  ...  77.505492             79.865439
-23  3072.0  80.202695  ...  83.886078             83.391907
-24  3200.0  82.262212  ...  89.385477             87.074829
-25  3328.0  83.226931  ...  86.946008             81.715431
-26  3456.0  78.578525  ...  84.420490             84.068369
-27  3584.0  87.296493  ...  90.276496             85.064084
-28  3712.0  83.386762  ...  83.876864             84.515517
-29  3840.0  85.005380  ...  87.701820             87.493673
-30  3968.0  92.864488  ...  84.562670             83.807647
-31  4096.0  93.596744  ...  83.626378             91.616198
+10  1408.0  64.138541  ...  66.485074             65.684049
+11  1536.0  80.430545  ...  76.106321             76.106321
+12  1664.0  63.372618  ...  62.061463             60.803457
+13  1792.0  72.512412  ...  68.953520             68.533074
+14  1920.0  69.120002  ...  69.467336             68.776119
+15  2048.0  73.584279  ...  75.915006             75.915006
+16  2176.0  83.500614  ...  80.817862             80.494588
+17  2304.0  68.446623  ...  72.828879             72.607513
+18  2432.0  71.125224  ...  79.139336             79.813818
+19  2560.0  77.833728  ...  76.740048             75.328737
+20  2688.0  84.108772  ...  79.524227             83.369354
+21  2816.0  82.135981  ...  78.868366             76.516158
+22  2944.0  81.967162  ...  81.034195             79.737653
+23  3072.0  81.825298  ...  83.146995             83.761985
+24  3200.0  84.210524  ...  89.887639             86.137280
+25  3328.0  82.464255  ...  82.843841             86.424125
+26  3456.0  82.604067  ...  87.442050             82.435141
+27  3584.0  86.540320  ...  96.683219             90.458141
+28  3712.0  84.946722  ...  82.084920             87.170458
+29  3840.0  84.421376  ...  86.806905             86.063813
+30  3968.0  92.652949  ...  87.472354             87.284643
+31  4096.0  93.401342  ...  91.553703             91.678778
 
 [32 rows x 5 columns]
 </pre></div>
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