[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 ... 15.420235 16.384000
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0 256.0 2.730667 ... 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 15.420235
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3 640.0 22.260869 ... 24.380953 24.380953
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4 768.0 32.768000 ... 34.028308 34.028308
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5 896.0 37.971025 ... 40.140799 39.025776
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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 45.242181 ... 48.161033 47.396572
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8 1280.0 51.200001 ... 57.690139 57.690139
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9 1408.0 64.138541 ... 68.147202 66.485074
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10 1536.0 79.526831 ... 81.355034 79.526831
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11 1664.0 62.929456 ... 63.372618 62.492442
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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 ... 73.460287 59.467852
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13 1920.0 69.120002 ... 71.257735 70.892307
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13 1920.0 69.467336 ... 71.257735 70.892307
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14 2048.0 73.262953 ... 78.033565 76.959706
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15 2176.0 83.155572 ... 87.876193 86.367588
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15 2176.0 83.155572 ... 87.494120 85.632545
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16 2304.0 68.446623 ... 78.064941 77.057651
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17 2432.0 71.305746 ... 86.711310 75.118889
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18 2560.0 77.833728 ... 82.956960 81.310171
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19 2688.0 83.922689 ... 90.316801 89.254248
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20 2816.0 83.712490 ... 84.360174 83.392363
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21 2944.0 81.698415 ... 83.477440 82.509987
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22 3072.0 82.420822 ... 90.020831 89.030036
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23 3200.0 84.768213 ... 97.859331 95.380032
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24 3328.0 83.034941 ... 86.011103 83.613586
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25 3456.0 80.945348 ... 87.158452 81.105671
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26 3584.0 87.211821 ... 99.354022 91.844118
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27 3712.0 84.159518 ... 88.955779 88.483034
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28 3840.0 84.292684 ... 93.484358 84.483849
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29 3968.0 92.688139 ... 85.093402 91.472214
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30 4096.0 86.620022 ... 88.621807 91.366730
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17 2432.0 71.305746 ... 86.711310 85.393507
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18 2560.0 77.833728 ... 82.331658 81.512437
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19 2688.0 83.922689 ... 90.748936 88.836198
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20 2816.0 79.879498 ... 84.197315 82.446516
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21 2944.0 82.509987 ... 83.198715 81.967162
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22 3072.0 82.062468 ... 88.750943 87.516392
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23 3200.0 84.880639 ... 93.158662 93.841640
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24 3328.0 81.530349 ... 85.857242 84.298943
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25 3456.0 82.435141 ... 91.771848 90.892410
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26 3584.0 85.552231 ... 88.496679 87.381330
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27 3712.0 85.675250 ... 93.187820 87.706180
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28 3840.0 81.798814 ... 90.723546 86.535214
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29 3968.0 89.921841 ... 85.451873 88.040360
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30 4096.0 92.691803 ... 93.271527 87.381330
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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 12.160 seconds)
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**Total running time of the script:** ( 6 minutes 9.590 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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