[GH-PAGES] Updated website
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@@ -459,37 +459,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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matmul-performance:
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M cuBLAS ... Triton Triton (+ LeakyReLU)
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0 256.0 2.730667 ... 3.276800 3.276800
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1 384.0 7.372800 ... 7.899428 7.899428
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2 512.0 14.563555 ... 16.384000 15.420235
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0 256.0 2.978909 ... 3.276800 2.978909
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1 384.0 7.372800 ... 8.507077 8.507077
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2 512.0 14.563555 ... 15.420235 16.384000
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3 640.0 22.260869 ... 24.380953 24.380953
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4 768.0 32.768000 ... 35.389441 34.028308
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5 896.0 39.025776 ... 40.140799 39.025776
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6 1024.0 49.932191 ... 53.773130 52.428801
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7 1152.0 44.566925 ... 48.161033 47.396572
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7 1152.0 44.566925 ... 48.161033 48.161033
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8 1280.0 51.200001 ... 57.690139 57.690139
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9 1408.0 64.138541 ... 69.009825 68.147202
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10 1536.0 80.430545 ... 81.355034 79.526831
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11 1664.0 63.372618 ... 63.372618 62.492442
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12 1792.0 72.983276 ... 73.943582 59.467852
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13 1920.0 69.467336 ... 71.257735 71.257735
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14 2048.0 73.584279 ... 78.398206 77.314362
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15 2176.0 83.500614 ... 87.876193 86.367588
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11 1664.0 63.372618 ... 63.372618 62.929456
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12 1792.0 72.983276 ... 73.460287 59.467852
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13 1920.0 68.776119 ... 71.257735 71.257735
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14 2048.0 73.908442 ... 78.398206 77.314362
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15 2176.0 83.500614 ... 87.494120 86.367588
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16 2304.0 68.251065 ... 78.064941 77.307030
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17 2432.0 71.305746 ... 86.444504 84.621881
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18 2560.0 78.019048 ... 82.331658 81.108913
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19 2688.0 83.369354 ... 90.966561 89.464755
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20 2816.0 79.587973 ... 84.197315 83.074685
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21 2944.0 81.967162 ... 83.060049 82.784108
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22 3072.0 82.420822 ... 87.924073 85.019675
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23 3200.0 84.768213 ... 96.458178 95.238096
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24 3328.0 83.905938 ... 85.096096 84.298943
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25 3456.0 82.604067 ... 91.304157 87.442050
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26 3584.0 87.211821 ... 98.375705 91.656871
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27 3712.0 84.874549 ... 89.035062 86.044224
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28 3840.0 84.744825 ... 93.484358 84.484863
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29 3968.0 92.582651 ... 84.976733 91.472214
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30 4096.0 86.256445 ... 88.475759 90.230403
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17 2432.0 71.305746 ... 85.915795 83.864074
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18 2560.0 78.019048 ... 82.747477 81.715711
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19 2688.0 83.922689 ... 91.185232 89.254248
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20 2816.0 80.026067 ... 83.712490 83.074685
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21 2944.0 82.102191 ... 82.921853 82.784108
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22 3072.0 81.884457 ... 89.310890 88.612060
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23 3200.0 83.879425 ... 96.096095 93.704243
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24 3328.0 84.101981 ... 85.602017 85.806075
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25 3456.0 81.435930 ... 90.687926 90.994998
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26 3584.0 87.042978 ... 93.273228 96.683219
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27 3712.0 85.822459 ... 88.876645 87.094458
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28 3840.0 81.798814 ... 88.050954 88.971840
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29 3968.0 92.758598 ... 85.871877 91.301109
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30 4096.0 86.536250 ... 87.041329 91.304576
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[31 rows x 5 columns]
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@@ -499,7 +499,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 6 minutes 18.355 seconds)
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**Total running time of the script:** ( 6 minutes 32.425 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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