[GH-PAGES] Updated website
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@@ -339,7 +339,7 @@ for different problem sizes.</p>
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15 134217728.0 849.737435 850.656574
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</pre></div>
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 39.455 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 41.915 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-01-vector-add-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<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>
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@@ -374,17 +374,17 @@ We will then compare its performance against (1) <code class="code docutils lite
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<p class="sphx-glr-script-out">Out:</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>softmax-performance:
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N Triton Torch (native) Torch (jit)
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0 256.0 512.000001 546.133347 186.181817
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0 256.0 512.000001 546.133347 190.511628
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1 384.0 614.400016 585.142862 153.600004
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2 512.0 655.360017 606.814814 154.566038
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3 640.0 682.666684 640.000002 160.000000
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4 768.0 722.823517 664.216187 162.754967
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.. ... ... ... ...
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93 12160.0 814.058574 406.179533 198.530610
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94 12288.0 814.111783 415.661740 198.895304
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95 12416.0 812.498981 412.149375 198.457532
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96 12544.0 812.566838 412.971190 198.667643
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97 12672.0 812.633240 412.097543 198.679085
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93 12160.0 814.058574 406.179533 198.631953
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94 12288.0 814.111783 415.661740 198.995960
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95 12416.0 812.498981 412.149375 198.556711
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96 12544.0 812.566838 412.971190 198.815254
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97 12672.0 812.633240 412.097543 198.873965
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[98 rows x 4 columns]
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</pre></div>
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@@ -397,7 +397,7 @@ We will then compare its performance against (1) <code class="code docutils lite
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Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li>
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</ul>
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</div></blockquote>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.411 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 23.388 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<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>
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@@ -568,7 +568,7 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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<p class="sphx-glr-script-out">Out:</p>
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<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
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M cuBLAS ... Triton Triton (+ LeakyReLU)
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0 256.0 2.978909 ... 2.978909 2.978909
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0 256.0 2.978909 ... 3.276800 3.276800
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1 384.0 7.372800 ... 8.507077 8.507077
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2 512.0 14.563555 ... 16.384000 16.384000
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3 640.0 22.260869 ... 24.380953 24.380953
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@@ -581,29 +581,29 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
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10 1536.0 80.430545 ... 79.526831 79.526831
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11 1664.0 62.929456 ... 62.492442 62.061463
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12 1792.0 72.512412 ... 72.512412 71.588687
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13 1920.0 68.776119 ... 70.172588 70.172588
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14 2048.0 73.584279 ... 76.959706 76.959706
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13 1920.0 69.120002 ... 70.172588 70.172588
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14 2048.0 73.908442 ... 76.608294 76.959706
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15 2176.0 83.500614 ... 86.367588 85.632545
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16 2304.0 68.643310 ... 77.057651 76.563695
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17 2432.0 71.305746 ... 85.134737 84.621881
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18 2560.0 77.833728 ... 81.108913 80.908642
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19 2688.0 83.186525 ... 89.888756 89.464755
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20 2816.0 83.312714 ... 82.916747 83.233226
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21 2944.0 82.509987 ... 82.373605 81.298583
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22 3072.0 81.121923 ... 88.197981 87.651868
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23 3200.0 83.989503 ... 95.665176 94.534716
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24 3328.0 83.034941 ... 84.101981 84.200347
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25 3456.0 81.932484 ... 83.286746 86.876687
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26 3584.0 87.296493 ... 97.628001 98.375705
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27 3712.0 81.615477 ... 87.094458 87.437503
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28 3840.0 82.716526 ... 90.132027 90.352941
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29 3968.0 87.976885 ... 91.062642 85.811488
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30 4096.0 93.142072 ... 91.366730 85.270056
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16 2304.0 68.643310 ... 76.809875 76.563695
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17 2432.0 71.305746 ... 85.134737 84.115159
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18 2560.0 77.283019 ... 81.108913 80.908642
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19 2688.0 83.369354 ... 89.888756 89.676257
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20 2816.0 83.074685 ... 83.074685 82.446516
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21 2944.0 81.967162 ... 81.698415 81.967162
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22 3072.0 82.301023 ... 88.750943 87.787755
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23 3200.0 82.368085 ... 91.954023 91.822093
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24 3328.0 80.798314 ... 84.101981 85.602017
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25 3456.0 81.766291 ... 91.511426 91.097818
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26 3584.0 84.033077 ... 91.563533 94.548254
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27 3712.0 85.528545 ... 86.264806 87.284705
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28 3840.0 85.005380 ... 91.701494 85.169042
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29 3968.0 92.267631 ... 83.865247 90.724116
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30 4096.0 86.426548 ... 87.097813 89.478485
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[31 rows x 5 columns]
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</pre></div>
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 25.507 seconds)</p>
|
||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 5 minutes 27.265 seconds)</p>
|
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-03-matrix-multiplication-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
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<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>
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|
@@ -197,32 +197,32 @@ to download the full example code</p>
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2 2048.0 423.724127 161.684218 334.367350
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3 2560.0 465.454542 181.775141 330.322572
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4 3072.0 515.580429 192.501302 320.556515
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3 2560.0 465.454542 181.238943 330.322572
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4 3072.0 511.999982 192.501302 320.556515
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5 3584.0 551.384634 208.271186 311.652167
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6 4096.0 568.231237 220.412561 298.796351
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9 5632.0 542.843364 243.545956 290.060087
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15 8704.0 417.791980 267.472468 284.987724
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16 9216.0 430.319054 272.394084 288.751954
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17 9728.0 438.857162 280.278512 289.667485
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18 10240.0 447.650282 286.433562 290.840246
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19 10752.0 428.651173 247.172406 290.922209
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17 9728.0 438.857162 280.615388 290.027323
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18 10240.0 447.650282 286.433562 290.153487
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19 10752.0 428.651173 246.935876 290.922209
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20 11264.0 429.786952 245.760001 286.676558
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21 11776.0 422.457417 249.888595 288.981596
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22 12288.0 420.102570 254.673582 294.617366
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23 12800.0 414.574901 253.674644 288.450715
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24 13312.0 412.242569 252.659556 289.916513
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25 13824.0 406.090579 257.390218 292.056329
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26 14336.0 396.387109 254.297107 286.959121
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27 14848.0 386.498925 257.665934 289.481735
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28 15360.0 373.495460 257.970599 287.550706
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21 11776.0 423.089806 249.667843 288.686414
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22 12288.0 420.102570 254.453844 294.617366
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23 12800.0 415.135142 253.465340 288.180121
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24 13312.0 412.242569 252.759501 289.916513
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25 13824.0 406.090579 257.190689 292.056329
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26 14336.0 395.930964 254.485198 286.959121
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27 14848.0 386.918555 257.479779 289.481735
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28 15360.0 373.117425 257.790220 287.550706
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29 15872.0 370.192407 261.806182 289.899545
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</pre></div>
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</div>
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@@ -477,7 +477,7 @@ to download the full example code</p>
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<span class="n">bench_layer_norm</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">save_path</span><span class="o">=</span><span class="s1">'.'</span><span class="p">,</span> <span class="n">print_data</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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</pre></div>
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</div>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 13.083 seconds)</p>
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||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 2 minutes 12.428 seconds)</p>
|
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-05-layer-norm-py">
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||||
<div class="sphx-glr-download sphx-glr-download-python docutils container">
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||||
<p><a class="reference download internal" download="" href="../../_downloads/935c0dd0fbeb4b2e69588471cbb2d4b2/05-layer-norm.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">05-layer-norm.py</span></code></a></p>
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@@ -174,7 +174,7 @@
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<div class="section" id="computation-times">
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<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>
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<p><strong>12:41.467</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
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<p><strong>12:45.006</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
|
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<table class="docutils align-default">
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<colgroup>
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<col style="width: 85%" />
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@@ -183,19 +183,19 @@
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</colgroup>
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<tbody>
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<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>
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<td><p>05:25.507</p></td>
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<td><p>05:27.265</p></td>
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<td><p>0.0 MB</p></td>
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||||
</tr>
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<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>
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<td><p>03:23.411</p></td>
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<td><p>03:23.388</p></td>
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<td><p>0.0 MB</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="05-layer-norm.html#sphx-glr-getting-started-tutorials-05-layer-norm-py"><span class="std std-ref">Layer Normalization</span></a> (<code class="docutils literal notranslate"><span class="pre">05-layer-norm.py</span></code>)</p></td>
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<td><p>02:13.083</p></td>
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<td><p>02:12.428</p></td>
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<td><p>0.0 MB</p></td>
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</tr>
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<tr class="row-even"><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>
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<td><p>01:39.455</p></td>
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<td><p>01:41.915</p></td>
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<td><p>0.0 MB</p></td>
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</tr>
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<tr class="row-odd"><td><p><a class="reference internal" href="04-low-memory-dropout.html#sphx-glr-getting-started-tutorials-04-low-memory-dropout-py"><span class="std std-ref">Low-Memory Dropout</span></a> (<code class="docutils literal notranslate"><span class="pre">04-low-memory-dropout.py</span></code>)</p></td>
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