[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 ... 8.507077 8.507077
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2 512.0 14.563555 ... 16.384000 15.420235
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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 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 37.971025 ... 40.140799 39.025776
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6 1024.0 49.932191 ... 53.773130 53.092457
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7 1152.0 45.242181 ... 48.161033 48.161033
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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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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 ... 69.009825 67.305878
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10 1536.0 80.430545 ... 81.355034 79.526831
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10 1536.0 80.430545 ... 80.430545 78.643199
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11 1664.0 62.929456 ... 63.372618 62.492442
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12 1792.0 72.512412 ... 73.460287 59.467852
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13 1920.0 69.120002 ... 71.626943 71.257735
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14 2048.0 73.908442 ... 78.398206 77.314362
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15 2176.0 83.500614 ... 87.876193 85.998493
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16 2304.0 68.446623 ... 78.064941 77.057651
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17 2432.0 71.305746 ... 85.393507 75.522751
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18 2560.0 77.833728 ... 82.125311 80.908642
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19 2688.0 83.922689 ... 90.966561 89.464755
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20 2816.0 81.067298 ... 84.360174 83.873477
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21 2944.0 81.967162 ... 83.337844 81.832567
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22 3072.0 82.420822 ... 89.310890 88.473602
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23 3200.0 83.879425 ... 95.238096 87.671229
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24 3328.0 82.369902 ... 85.602017 81.994643
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25 3456.0 80.864158 ... 84.332184 90.281712
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26 3584.0 87.127323 ... 97.947050 97.205829
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27 3712.0 84.159518 ... 89.035062 87.552452
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28 3840.0 81.138664 ... 86.332554 90.279183
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29 3968.0 87.913500 ... 91.954739 86.358055
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30 4096.0 93.271527 ... 84.254693 82.418802
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13 1920.0 69.120002 ... 71.257735 71.257735
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14 2048.0 73.908442 ... 78.033565 77.314362
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15 2176.0 83.500614 ... 87.494120 86.367588
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16 2304.0 68.446623 ... 77.810656 77.307030
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17 2432.0 71.305746 ... 85.915795 85.653855
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18 2560.0 77.833728 ... 82.331658 81.108913
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19 2688.0 83.552988 ... 90.966561 89.888756
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20 2816.0 80.026067 ... 84.197315 83.712490
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21 2944.0 82.102191 ... 83.617504 82.509987
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22 3072.0 81.825298 ... 89.451983 88.197981
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23 3200.0 84.432717 ... 96.822991 95.808380
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24 3328.0 83.226931 ... 85.398926 84.795401
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25 3456.0 81.932484 ... 91.928814 88.400840
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26 3584.0 86.540320 ... 98.375705 97.311031
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27 3712.0 84.159518 ... 89.273764 86.118401
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28 3840.0 84.132370 ... 93.012618 85.863352
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29 3968.0 91.747320 ... 85.004484 87.881842
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30 4096.0 92.820009 ... 91.804194 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:** ( 7 minutes 19.813 seconds)
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**Total running time of the script:** ( 7 minutes 5.808 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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