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
index 49a147e4c..f9bd7f6a2 100644
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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 fc3c124e9..5c8aaa45c 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 2035d05d2..5af2325c7 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 6631f74f8..2bbbe1852 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 69a3b5b81..9ea8907b5 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 7d4485ffb..e49c75656 100644
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diff --git a/_images/sphx_glr_03-matrix-multiplication_thumb.png b/_images/sphx_glr_03-matrix-multiplication_thumb.png
index 8ca63624c..78a2830d7 100644
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diff --git a/_sources/getting-started/installation.rst.txt b/_sources/getting-started/installation.rst.txt
index 658276db5..db6b6261b 100644
--- a/_sources/getting-started/installation.rst.txt
+++ b/_sources/getting-started/installation.rst.txt
@@ -45,7 +45,7 @@ You can then test your installation by running the unit tests:
 .. code-block:: bash
 
       pip install -r requirements-test.txt
-      pytest -vs .
+      pytest -vs test/unit/
 
 and the benchmarks
 
diff --git a/_sources/getting-started/tutorials/01-vector-add.rst.txt b/_sources/getting-started/tutorials/01-vector-add.rst.txt
index e9666f082..44b54dad5 100644
--- a/_sources/getting-started/tutorials/01-vector-add.rst.txt
+++ b/_sources/getting-started/tutorials/01-vector-add.rst.txt
@@ -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:** ( 1 minutes  50.209 seconds)
+   **Total running time of the script:** ( 1 minutes  45.270 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 5c18a8d55..16a70962d 100644
--- a/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
+++ b/_sources/getting-started/tutorials/02-fused-softmax.rst.txt
@@ -286,17 +286,17 @@ 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  512.000001      546.133347   184.089886
-    1     384.0  585.142862      585.142862   153.600004
-    2     512.0  630.153853      585.142849   154.566038
-    3     640.0  682.666684      640.000002   160.000000
-    4     768.0  702.171410      664.216187   163.839992
+    0     256.0  512.000001      546.133347   188.321838
+    1     384.0  585.142862      585.142862   151.703707
+    2     512.0  630.153853      585.142849   153.121496
+    3     640.0  682.666684      640.000002   158.759699
+    4     768.0  702.171410      664.216187   161.684218
     ..      ...         ...             ...          ...
-    93  12160.0  810.666687      405.755985   199.140227
-    94  12288.0  810.754644      415.661740   199.399583
-    95  12416.0  807.544681      411.296057   198.954424
-    96  12544.0  807.661970      412.971190   199.209928
-    97  12672.0  807.776923      412.097543   199.264875
+    93  12160.0  810.666687      405.755985   199.038365
+    94  12288.0  810.754644      415.661740   199.298541
+    95  12416.0  809.189387      412.149375   198.854847
+    96  12544.0  807.661970      412.971190   199.111113
+    97  12672.0  807.776923      412.307051   199.167004
 
     [98 rows x 4 columns]
 
@@ -314,7 +314,7 @@ In the above plot, we can see that:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 3 minutes  27.286 seconds)
+   **Total running time of the script:** ( 3 minutes  23.687 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 3f882d931..9a069a2cc 100644
--- a/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
+++ b/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt
@@ -462,7 +462,7 @@ 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  ...   3.276800              3.276800
+    0    256.0   2.730667  ...   2.978909              2.978909
     1    384.0   7.372800  ...   8.507077              8.507077
     2    512.0  14.563555  ...  16.384000             16.384000
     3    640.0  22.260869  ...  24.380953             24.380953
@@ -470,29 +470,29 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
     5    896.0  39.025776  ...  39.025776             39.025776
     6   1024.0  49.932191  ...  53.773130             52.428801
     7   1152.0  44.566925  ...  46.656000             46.656000
-    8   1280.0  51.200001  ...  56.109587             56.109587
-    9   1408.0  64.138541  ...  66.485074             66.485074
-    10  1536.0  80.430545  ...  79.526831             78.643199
-    11  1664.0  62.929456  ...  62.061463             62.061463
-    12  1792.0  72.983276  ...  72.047592             72.047592
-    13  1920.0  69.120002  ...  70.530615             70.172588
+    8   1280.0  51.200001  ...  56.888887             56.109587
+    9   1408.0  64.138541  ...  67.305878             67.305878
+    10  1536.0  80.430545  ...  79.526831             79.526831
+    11  1664.0  63.372618  ...  62.492442             62.492442
+    12  1792.0  72.983276  ...  72.512412             72.047592
+    13  1920.0  68.776119  ...  70.530615             70.530615
     14  2048.0  73.908442  ...  76.959706             76.608294
-    15  2176.0  83.500614  ...  86.367588             85.998493
-    16  2304.0  68.446623  ...  77.057651             77.057651
-    17  2432.0  71.305746  ...  85.393507             84.877538
-    18  2560.0  78.019048  ...  81.310171             81.310171
-    19  2688.0  83.737433  ...  89.254248             89.888756
-    20  2816.0  82.602666  ...  83.074685             83.233226
-    21  2944.0  82.237674  ...  82.784108             82.509987
-    22  3072.0  82.661468  ...  88.750943             85.920732
-    23  3200.0  84.993363  ...  90.780140             95.522391
-    24  3328.0  83.613586  ...  81.346098             83.905938
-    25  3456.0  81.849303  ...  91.304157             87.823058
-    26  3584.0  83.024371  ...  94.747514             95.451583
-    27  3712.0  81.682211  ...  87.937800             87.937800
-    28  3840.0  82.778440  ...  90.723546             88.473602
-    29  3968.0  91.747320  ...  84.038524             91.335278
-    30  4096.0  91.741443  ...  85.001726             90.200084
+    15  2176.0  83.500614  ...  86.367588             84.909907
+    16  2304.0  68.446623  ...  76.563695             76.809875
+    17  2432.0  71.305746  ...  74.521127             85.134737
+    18  2560.0  77.649287  ...  81.512437             80.709358
+    19  2688.0  83.552988  ...  89.254248             89.570381
+    20  2816.0  82.759409  ...  82.916747             83.233226
+    21  2944.0  82.921853  ...  82.373605             82.921853
+    22  3072.0  82.062468  ...  88.335577             89.170242
+    23  3200.0  84.768213  ...  95.380032             95.238096
+    24  3328.0  83.130825  ...  85.398926             85.500351
+    25  3456.0  80.945348  ...  82.350937             85.950501
+    26  3584.0  86.958797  ...  98.916823             98.160909
+    27  3712.0  81.482335  ...  87.629253             87.170458
+    28  3840.0  84.615146  ...  91.930177             84.615146
+    29  3968.0  92.163097  ...  80.998301             84.562670
+    30  4096.0  88.534120  ...  83.520676             84.360608
 
     [31 rows x 5 columns]
 
@@ -502,7 +502,7 @@ 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:** ( 5 minutes  37.929 seconds)
+   **Total running time of the script:** ( 5 minutes  36.208 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 4d958b48f..4ba647f00 100644
--- a/_sources/getting-started/tutorials/sg_execution_times.rst.txt
+++ b/_sources/getting-started/tutorials/sg_execution_times.rst.txt
@@ -5,14 +5,14 @@
 
 Computation times
 =================
-**10:55.434** total execution time for **getting-started_tutorials** files:
+**10:45.175** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:37.929 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:36.208 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:27.286 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:23.687 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:50.209 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:45.270 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.010 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
diff --git a/getting-started/installation.html b/getting-started/installation.html
index 5e2068b44..2a523db99 100644
--- a/getting-started/installation.html
+++ b/getting-started/installation.html
@@ -209,7 +209,7 @@ pip install -e .
 <p>Note that, if llvm-11 is not present on your system, the setup.py script will download the official LLVM11 static libraries link against that.</p>
 <p>You can then test your installation by running the unit tests:</p>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip install -r requirements-test.txt
-pytest -vs .
+pytest -vs test/unit/
 </pre></div>
 </div>
 <p>and the benchmarks</p>
diff --git a/getting-started/tutorials/01-vector-add.html b/getting-started/tutorials/01-vector-add.html
index 7c7b4d080..00fd1faa7 100644
--- a/getting-started/tutorials/01-vector-add.html
+++ b/getting-started/tutorials/01-vector-add.html
@@ -338,7 +338,7 @@ 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  50.209 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  45.270 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 31a0f0694..5bb21bb75 100644
--- a/getting-started/tutorials/02-fused-softmax.html
+++ b/getting-started/tutorials/02-fused-softmax.html
@@ -373,17 +373,17 @@ 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  512.000001      546.133347   184.089886
-1     384.0  585.142862      585.142862   153.600004
-2     512.0  630.153853      585.142849   154.566038
-3     640.0  682.666684      640.000002   160.000000
-4     768.0  702.171410      664.216187   163.839992
+0     256.0  512.000001      546.133347   188.321838
+1     384.0  585.142862      585.142862   151.703707
+2     512.0  630.153853      585.142849   153.121496
+3     640.0  682.666684      640.000002   158.759699
+4     768.0  702.171410      664.216187   161.684218
 ..      ...         ...             ...          ...
-93  12160.0  810.666687      405.755985   199.140227
-94  12288.0  810.754644      415.661740   199.399583
-95  12416.0  807.544681      411.296057   198.954424
-96  12544.0  807.661970      412.971190   199.209928
-97  12672.0  807.776923      412.097543   199.264875
+93  12160.0  810.666687      405.755985   199.038365
+94  12288.0  810.754644      415.661740   199.298541
+95  12416.0  809.189387      412.149375   198.854847
+96  12544.0  807.661970      412.971190   199.111113
+97  12672.0  807.776923      412.307051   199.167004
 
 [98 rows x 4 columns]
 </pre></div>
@@ -396,7 +396,7 @@ 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  27.286 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  23.687 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 e7f33a75e..301dc3f0d 100644
--- a/getting-started/tutorials/03-matrix-multiplication.html
+++ b/getting-started/tutorials/03-matrix-multiplication.html
@@ -567,7 +567,7 @@ 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  ...   3.276800              3.276800
+0    256.0   2.730667  ...   2.978909              2.978909
 1    384.0   7.372800  ...   8.507077              8.507077
 2    512.0  14.563555  ...  16.384000             16.384000
 3    640.0  22.260869  ...  24.380953             24.380953
@@ -575,34 +575,34 @@ torch_output=tensor([[  1.1045, -36.9688,  31.4688,  ..., -11.3906,  24.4531, -3
 5    896.0  39.025776  ...  39.025776             39.025776
 6   1024.0  49.932191  ...  53.773130             52.428801
 7   1152.0  44.566925  ...  46.656000             46.656000
-8   1280.0  51.200001  ...  56.109587             56.109587
-9   1408.0  64.138541  ...  66.485074             66.485074
-10  1536.0  80.430545  ...  79.526831             78.643199
-11  1664.0  62.929456  ...  62.061463             62.061463
-12  1792.0  72.983276  ...  72.047592             72.047592
-13  1920.0  69.120002  ...  70.530615             70.172588
+8   1280.0  51.200001  ...  56.888887             56.109587
+9   1408.0  64.138541  ...  67.305878             67.305878
+10  1536.0  80.430545  ...  79.526831             79.526831
+11  1664.0  63.372618  ...  62.492442             62.492442
+12  1792.0  72.983276  ...  72.512412             72.047592
+13  1920.0  68.776119  ...  70.530615             70.530615
 14  2048.0  73.908442  ...  76.959706             76.608294
-15  2176.0  83.500614  ...  86.367588             85.998493
-16  2304.0  68.446623  ...  77.057651             77.057651
-17  2432.0  71.305746  ...  85.393507             84.877538
-18  2560.0  78.019048  ...  81.310171             81.310171
-19  2688.0  83.737433  ...  89.254248             89.888756
-20  2816.0  82.602666  ...  83.074685             83.233226
-21  2944.0  82.237674  ...  82.784108             82.509987
-22  3072.0  82.661468  ...  88.750943             85.920732
-23  3200.0  84.993363  ...  90.780140             95.522391
-24  3328.0  83.613586  ...  81.346098             83.905938
-25  3456.0  81.849303  ...  91.304157             87.823058
-26  3584.0  83.024371  ...  94.747514             95.451583
-27  3712.0  81.682211  ...  87.937800             87.937800
-28  3840.0  82.778440  ...  90.723546             88.473602
-29  3968.0  91.747320  ...  84.038524             91.335278
-30  4096.0  91.741443  ...  85.001726             90.200084
+15  2176.0  83.500614  ...  86.367588             84.909907
+16  2304.0  68.446623  ...  76.563695             76.809875
+17  2432.0  71.305746  ...  74.521127             85.134737
+18  2560.0  77.649287  ...  81.512437             80.709358
+19  2688.0  83.552988  ...  89.254248             89.570381
+20  2816.0  82.759409  ...  82.916747             83.233226
+21  2944.0  82.921853  ...  82.373605             82.921853
+22  3072.0  82.062468  ...  88.335577             89.170242
+23  3200.0  84.768213  ...  95.380032             95.238096
+24  3328.0  83.130825  ...  85.398926             85.500351
+25  3456.0  80.945348  ...  82.350937             85.950501
+26  3584.0  86.958797  ...  98.916823             98.160909
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