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 a23b004e0..6f57c7355 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 0b63763c9..897d63fc1 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 93ddee2d3..dc9b5ba5c 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 c76e7560a..39b715c99 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 84979b1b0..1a8fd34bf 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 8acc66163..0f098002f 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 aad574e3d..510bdb66e 100644
--- a/_sources/getting-started/tutorials/01-vector-add.rst.txt
+++ b/_sources/getting-started/tutorials/01-vector-add.rst.txt
@@ -232,9 +232,9 @@ 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    9.600000    9.600000
-    1        8192.0   15.999999   19.200000
+    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   76.800002
     4       65536.0  127.999995  127.999995
     5      131072.0  219.428568  219.428568
     6      262144.0  341.333321  341.333321
@@ -254,7 +254,7 @@ 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  11.024 seconds)
+   **Total running time of the script:** ( 0 minutes  10.996 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 8b99f7293..896d66447 100644
--- a/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
+++ b/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
@@ -301,16 +301,16 @@ 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  512.000001      546.133347   186.181817
-    1     384.0  585.142862      558.545450   151.703707
-    2     512.0  630.153853      585.142849   154.566038
+    1     384.0  585.142862      585.142862   153.600004
+    2     512.0  630.153853      606.814814   154.566038
     3     640.0  682.666684      640.000002   160.000000
     4     768.0  702.171410      664.216187   163.839992
     ..      ...         ...             ...          ...
     93  12160.0  812.359066      406.179533   199.038365
-    94  12288.0  812.429770      415.222812   199.399583
-    95  12416.0  810.840807      412.149375   198.854847
-    96  12544.0  809.290334      412.971190   199.209928
-    97  12672.0  809.389265      412.097543   199.362843
+    94  12288.0  812.429770      415.661740   199.298541
+    95  12416.0  810.840807      412.149375   198.954424
+    96  12544.0  810.925276      412.971190   199.209928
+    97  12672.0  809.389265      412.097543   199.167004
 
     [98 rows x 4 columns]
 
@@ -328,7 +328,7 @@ In the above plot, we can see that:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  12.613 seconds)
+   **Total running time of the script:** ( 1 minutes  12.689 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 a1570acc4..fcb4e76b2 100644
--- a/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
+++ b/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
@@ -463,37 +463,37 @@ 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   2.978909  ...   2.978909              2.978909
-    2    384.0   7.372800  ...   8.507077              8.507077
-    3    512.0  14.563555  ...  16.384000             15.420235
+    1    256.0   2.978909  ...   3.276800              2.978909
+    2    384.0   7.372800  ...   7.899428              7.899428
+    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  37.971025  ...  40.140799             39.025776
-    7   1024.0  49.932191  ...  52.428801             52.428801
+    6    896.0  39.025776  ...  40.140799             39.025776
+    7   1024.0  49.932191  ...  53.773130             52.428801
     8   1152.0  44.566925  ...  46.656000             46.656000
     9   1280.0  51.200001  ...  56.888887             56.109587
-    10  1408.0  64.138541  ...  64.902096             64.902096
-    11  1536.0  80.430545  ...  76.933564             76.106321
-    12  1664.0  63.372618  ...  62.492442             62.492442
-    13  1792.0  72.983276  ...  70.246402             69.810085
-    14  1920.0  69.467336  ...  70.892307             70.530615
-    15  2048.0  73.908442  ...  75.234154             74.898285
-    16  2176.0  83.500614  ...  80.817862             80.173899
-    17  2304.0  68.446623  ...  73.501144             73.051599
-    18  2432.0  71.125224  ...  80.499895             79.587714
-    19  2560.0  77.833728  ...  77.283019             76.740048
-    20  2688.0  84.108772  ...  83.552988             84.108772
-    21  2816.0  81.674548  ...  77.882512             79.733474
-    22  2944.0  81.832567  ...  78.235527             77.990663
-    23  3072.0  81.121923  ...  83.761985             80.544956
-    24  3200.0  84.768213  ...  89.635851             89.635851
-    25  3328.0  79.812967  ...  84.200347             87.580655
-    26  3456.0  81.189898  ...  84.420490             85.404201
-    27  3584.0  86.707226  ...  95.047985             90.549237
-    28  3712.0  84.159518  ...  84.301560             82.423549
-    29  3840.0  83.655065  ...  87.562949             87.493673
-    30  3968.0  93.076994  ...  88.040360             87.913500
-    31  4096.0  93.596744  ...  86.816123             83.571059
+    10  1408.0  64.138541  ...  64.902096             57.997615
+    11  1536.0  79.526831  ...  76.106321             75.296679
+    12  1664.0  62.929456  ...  62.061463             62.061463
+    13  1792.0  72.983276  ...  69.810085             69.379162
+    14  1920.0  69.120002  ...  68.098521             70.172588
+    15  2048.0  73.908442  ...  74.898285             74.565406
+    16  2176.0  83.500614  ...  77.998640             80.173899
+    17  2304.0  68.446623  ...  73.728002             73.275679
+    18  2432.0  71.305746  ...  82.147552             81.433227
+    19  2560.0  77.649287  ...  77.283019             75.502306
+    20  2688.0  83.369354  ...  83.186525             83.922689
+    21  2816.0  80.617762  ...  78.301990             79.879498
+    22  2944.0  82.102191  ...  79.356738             77.868802
+    23  3072.0  82.301023  ...  83.886078             79.750851
+    24  3200.0  84.432717  ...  90.267985             87.912086
+    25  3328.0  83.226931  ...  87.156532             82.653612
+    26  3456.0  81.026701  ...  84.244062             85.313831
+    27  3584.0  88.238857  ...  88.152348             90.640517
+    28  3712.0  85.382349  ...  81.816008             81.283434
+    29  3840.0  83.465663  ...  87.701820             87.493673
+    30  3968.0  93.148045  ...  88.103928             87.472354
+    31  4096.0  93.858555  ...  86.816123             90.139506
 
     [32 rows x 5 columns]
 
@@ -503,7 +503,7 @@ 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  2.006 seconds)
+   **Total running time of the script:** ( 2 minutes  22.200 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 9426fe390..844a2de4e 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
 =================
-**03:25.643** total execution time for **getting-started_tutorials** files:
+**03:45.884** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:02.006 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:22.200 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 01:12.613 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 01:12.689 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 00:11.024 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 00:10.996 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/getting-started/tutorials/01-vector-add.html b/getting-started/tutorials/01-vector-add.html
index d85ee463c..2aa9596f8 100644
--- a/getting-started/tutorials/01-vector-add.html
+++ b/getting-started/tutorials/01-vector-add.html
@@ -320,9 +320,9 @@ for different problem sizes.</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    9.600000    9.600000
-1        8192.0   15.999999   19.200000
+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   76.800002
 4       65536.0  127.999995  127.999995
 5      131072.0  219.428568  219.428568
 6      262144.0  341.333321  341.333321
@@ -337,7 +337,7 @@ 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  11.024 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  10.996 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 791a502e3..526f2a7bd 100644
--- a/getting-started/tutorials/02-fused-softmax.html
+++ b/getting-started/tutorials/02-fused-softmax.html
@@ -386,16 +386,16 @@ 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  512.000001      546.133347   186.181817
-1     384.0  585.142862      558.545450   151.703707
-2     512.0  630.153853      585.142849   154.566038
+1     384.0  585.142862      585.142862   153.600004
+2     512.0  630.153853      606.814814   154.566038
 3     640.0  682.666684      640.000002   160.000000
 4     768.0  702.171410      664.216187   163.839992
 ..      ...         ...             ...          ...
 93  12160.0  812.359066      406.179533   199.038365
-94  12288.0  812.429770      415.222812   199.399583
-95  12416.0  810.840807      412.149375   198.854847
-96  12544.0  809.290334      412.971190   199.209928
-97  12672.0  809.389265      412.097543   199.362843
+94  12288.0  812.429770      415.661740   199.298541
+95  12416.0  810.840807      412.149375   198.954424
+96  12544.0  810.925276      412.971190   199.209928
+97  12672.0  809.389265      412.097543   199.167004
 
 [98 rows x 4 columns]
 </pre></div>
@@ -408,7 +408,7 @@ 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> ( 1 minutes  12.613 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  12.689 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 ba739ef6b..aadb27222 100644
--- a/getting-started/tutorials/03-matrix-multiplication.html
+++ b/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
 <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   2.978909  ...   2.978909              2.978909
-2    384.0   7.372800  ...   8.507077              8.507077
-3    512.0  14.563555  ...  16.384000             15.420235
+1    256.0   2.978909  ...   3.276800              2.978909
+2    384.0   7.372800  ...   7.899428              7.899428
+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  37.971025  ...  40.140799             39.025776
-7   1024.0  49.932191  ...  52.428801             52.428801
+6    896.0  39.025776  ...  40.140799             39.025776
+7   1024.0  49.932191  ...  53.773130             52.428801
 8   1152.0  44.566925  ...  46.656000             46.656000
 9   1280.0  51.200001  ...  56.888887             56.109587
-10  1408.0  64.138541  ...  64.902096             64.902096
-11  1536.0  80.430545  ...  76.933564             76.106321
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-14  1920.0  69.467336  ...  70.892307             70.530615
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-17  2304.0  68.446623  ...  73.501144             73.051599
-18  2432.0  71.125224  ...  80.499895             79.587714
-19  2560.0  77.833728  ...  77.283019             76.740048
-20  2688.0  84.108772  ...  83.552988             84.108772
-21  2816.0  81.674548  ...  77.882512             79.733474
-22  2944.0  81.832567  ...  78.235527             77.990663
-23  3072.0  81.121923  ...  83.761985             80.544956
-24  3200.0  84.768213  ...  89.635851             89.635851
-25  3328.0  79.812967  ...  84.200347             87.580655
-26  3456.0  81.189898  ...  84.420490             85.404201
-27  3584.0  86.707226  ...  95.047985             90.549237
-28  3712.0  84.159518  ...  84.301560             82.423549
-29  3840.0  83.655065  ...  87.562949             87.493673
-30  3968.0  93.076994  ...  88.040360             87.913500
-31  4096.0  93.596744  ...  86.816123             83.571059
+10  1408.0  64.138541  ...  64.902096             57.997615
+11  1536.0  79.526831  ...  76.106321             75.296679
+12  1664.0  62.929456  ...  62.061463             62.061463
+13  1792.0  72.983276  ...  69.810085             69.379162
+14  1920.0  69.120002  ...  68.098521             70.172588
+15  2048.0  73.908442  ...  74.898285             74.565406
+16  2176.0  83.500614  ...  77.998640             80.173899
+17  2304.0  68.446623  ...  73.728002             73.275679
+18  2432.0  71.305746  ...  82.147552             81.433227
+19  2560.0  77.649287  ...  77.283019             75.502306
+20  2688.0  83.369354  ...  83.186525             83.922689
+21  2816.0  80.617762  ...  78.301990             79.879498
+22  2944.0  82.102191  ...  79.356738             77.868802
+23  3072.0  82.301023  ...  83.886078             79.750851
+24  3200.0  84.432717  ...  90.267985             87.912086
+25  3328.0  83.226931  ...  87.156532             82.653612
+26  3456.0  81.026701  ...  84.244062             85.313831
+27  3584.0  88.238857  ...  88.152348             90.640517
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