[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 ... 2.978909 3.276800
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1 384.0 7.372800 ... 7.899428 8.507077
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2 512.0 14.563555 ... 15.420235 16.384000
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0 256.0 2.730667 ... 2.978909 2.978909
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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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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 51.150050 ... 53.773130 52.428801
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5 896.0 37.971025 ... 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 67.305878
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10 1536.0 80.430545 ... 81.355034 79.526831
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10 1536.0 79.526831 ... 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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12 1792.0 72.983276 ... 72.983276 59.467852
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13 1920.0 69.120002 ... 71.257735 70.892307
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14 2048.0 73.908442 ... 78.398206 77.314362
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15 2176.0 83.155572 ... 88.261612 86.367588
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16 2304.0 68.446623 ... 78.064941 77.558029
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17 2432.0 71.305746 ... 86.711310 85.915795
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18 2560.0 78.019048 ... 82.539044 81.310171
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19 2688.0 83.552988 ... 90.102270 89.888756
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20 2816.0 83.712490 ... 84.852542 83.873477
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21 2944.0 82.373605 ... 83.758038 82.921853
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22 3072.0 82.540970 ... 85.922766 88.335577
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23 3200.0 84.993363 ... 96.676741 96.385543
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24 3328.0 84.003845 ... 86.217120 81.162679
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25 3456.0 81.026701 ... 85.767626 89.183149
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26 3584.0 87.211821 ... 99.463928 97.840469
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27 3712.0 83.247783 ... 89.273764 84.088676
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28 3840.0 85.070769 ... 90.723546 88.686451
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29 3968.0 93.219206 ... 88.103928 87.441013
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30 4096.0 90.565269 ... 86.037005 82.597115
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14 2048.0 73.584279 ... 78.398206 77.314362
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15 2176.0 83.155572 ... 87.494120 85.632545
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16 2304.0 68.446623 ... 78.064941 77.307030
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17 2432.0 71.305746 ... 86.711310 86.179335
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18 2560.0 78.019048 ... 82.331658 81.715711
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19 2688.0 83.369354 ... 90.532356 89.464755
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20 2816.0 84.360174 ... 84.687779 83.873477
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21 2944.0 82.373605 ... 83.758038 82.102191
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22 3072.0 82.540970 ... 89.593522 88.612060
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23 3200.0 84.544253 ... 96.822991 95.665176
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24 3328.0 83.905938 ... 85.398926 84.101981
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25 3456.0 82.773682 ... 86.318594 88.400840
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26 3584.0 86.457107 ... 97.416461 98.699661
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27 3712.0 83.317214 ... 88.955779 85.491947
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28 3840.0 84.036474 ... 93.801526 84.679936
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29 3968.0 93.576636 ... 81.025193 81.512316
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30 4096.0 88.475759 ... 93.858555 89.928129
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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:** ( 7 minutes 17.371 seconds)
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**Total running time of the script:** ( 7 minutes 24.521 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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