[GH-PAGES] Updated website
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@@ -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
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||||
2 16384.0 38.400001 38.400001
|
||||
3 32768.0 76.800002 76.800002
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||||
3 32768.0 63.999998 76.800002
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||||
4 65536.0 127.999995 127.999995
|
||||
5 131072.0 219.428568 219.428568
|
||||
6 262144.0 341.333321 341.333321
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||||
@@ -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:
|
||||
|
@@ -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
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||||
2 512.0 630.153853 606.814814 154.566038
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||||
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]
|
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|
||||
@@ -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:
|
||||
|
@@ -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
|
||||
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|
||||
7 1024.0 49.932191 ... 52.428801 52.428801
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||||
6 896.0 39.025776 ... 40.140799 39.025776
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7 1024.0 49.932191 ... 53.773130 52.428801
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||||
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:
|
||||
|
@@ -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 |
|
||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||
|
@@ -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>
|
||||
|
@@ -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>
|
||||
|
@@ -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
|
||||
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]
|
||||
</pre></div>
|
||||
</div>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 2.006 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 22.200 seconds)</p>
|
||||
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-03-matrix-multiplication-py">
|
||||
<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
||||
<p><a class="reference download internal" download="" href="../../_downloads/d5fee5b55a64e47f1b5724ec39adf171/03-matrix-multiplication.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">03-matrix-multiplication.py</span></code></a></p>
|
||||
|
@@ -174,7 +174,7 @@
|
||||
|
||||
<div class="section" id="computation-times">
|
||||
<span id="sphx-glr-getting-started-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
|
||||
<p><strong>03:25.643</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<p><strong>03:45.884</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
||||
<table class="docutils align-default">
|
||||
<colgroup>
|
||||
<col style="width: 85%" />
|
||||
@@ -183,15 +183,15 @@
|
||||
</colgroup>
|
||||
<tbody>
|
||||
<tr class="row-odd"><td><p><a class="reference internal" href="03-matrix-multiplication.html#sphx-glr-getting-started-tutorials-03-matrix-multiplication-py"><span class="std std-ref">Matrix Multiplication</span></a> (<code class="docutils literal notranslate"><span class="pre">03-matrix-multiplication.py</span></code>)</p></td>
|
||||
<td><p>02:02.006</p></td>
|
||||
<td><p>02:22.200</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-even"><td><p><a class="reference internal" href="02-fused-softmax.html#sphx-glr-getting-started-tutorials-02-fused-softmax-py"><span class="std std-ref">Fused Softmax</span></a> (<code class="docutils literal notranslate"><span class="pre">02-fused-softmax.py</span></code>)</p></td>
|
||||
<td><p>01:12.613</p></td>
|
||||
<td><p>01:12.689</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
<tr class="row-odd"><td><p><a class="reference internal" href="01-vector-add.html#sphx-glr-getting-started-tutorials-01-vector-add-py"><span class="std std-ref">Vector Addition</span></a> (<code class="docutils literal notranslate"><span class="pre">01-vector-add.py</span></code>)</p></td>
|
||||
<td><p>00:11.024</p></td>
|
||||
<td><p>00:10.996</p></td>
|
||||
<td><p>0.0 MB</p></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
|
@@ -198,13 +198,14 @@
|
||||
<h1>triton.language.atomic_xchg<a class="headerlink" href="#triton-language-atomic-xchg" title="Permalink to this headline">¶</a></h1>
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="triton.language.atomic_xchg">
|
||||
<span class="sig-prename descclassname"><span class="pre">triton.language.</span></span><span class="sig-name descname"><span class="pre">atomic_xchg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pointer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">builder</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#triton.language.atomic_xchg" title="Permalink to this definition">¶</a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">triton.language.</span></span><span class="sig-name descname"><span class="pre">atomic_xchg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pointer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">builder</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#triton.language.atomic_xchg" title="Permalink to this definition">¶</a></dt>
|
||||
<dd><p>Swaps the <em>old</em> values stored at location <code class="code docutils literal notranslate"><span class="pre">pointer</span></code> with the new values given by <code class="code docutils literal notranslate"><span class="pre">val</span></code>. Returns the old values.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters</dt>
|
||||
<dd class="field-odd"><ul class="simple">
|
||||
<li><p><strong>pointer</strong> (<em>Block of dtype=triton.PointerDType</em>) – The memory locations which contain the old values</p></li>
|
||||
<li><p><strong>val</strong> (<em>Block of dtype=`pointer.dtype.element_ty`</em>) – The new values to store</p></li>
|
||||
<li><p><strong>mask</strong> (<em>Block of triton.int1</em><em>, </em><em>optional</em>) – If mask[idx] is false, <code class="code docutils literal notranslate"><span class="pre">pointer[idx]</span></code> is unaffected.</p></li>
|
||||
<li><p><strong>builder</strong> (<em>triton.ir.builder</em><em>, </em><em>optional from within JIT'ed functions</em>) – IR builder to generate code into</p></li>
|
||||
</ul>
|
||||
</dd>
|
||||
|