[GH-PAGES] Updated website
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@@ -460,36 +460,36 @@ 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 2.978909 ... 3.276800 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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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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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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7 1152.0 45.242181 ... 47.396572 47.396572
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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 78.643199
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9 1408.0 64.138541 ... 69.009825 68.147202
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10 1536.0 80.430545 ... 80.430545 79.526831
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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 ... 71.257735 71.257735
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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 86.367588
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16 2304.0 68.446623 ... 78.064941 76.809875
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17 2432.0 71.305746 ... 85.915795 84.621881
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18 2560.0 78.019048 ... 82.539044 81.310171
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19 2688.0 83.369354 ... 90.748936 89.254248
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20 2816.0 79.733474 ... 84.197315 83.712490
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21 2944.0 79.610276 ... 83.060049 82.102191
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22 3072.0 82.301023 ... 89.451983 88.197981
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23 3200.0 85.447263 ... 97.116842 95.380032
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24 3328.0 83.178850 ... 85.196803 84.695641
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25 3456.0 82.688790 ... 84.909497 81.274299
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26 3584.0 87.381330 ... 98.375705 98.591437
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27 3712.0 82.423549 ... 89.035062 87.552452
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28 3840.0 82.716526 ... 85.930069 90.058629
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29 3968.0 87.913500 ... 91.678389 85.212248
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30 4096.0 93.206754 ... 86.230472 89.958266
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15 2176.0 83.500614 ... 87.876193 85.998493
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16 2304.0 68.446623 ... 78.064941 77.307030
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17 2432.0 71.305746 ... 85.653855 83.119713
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18 2560.0 77.833728 ... 82.539044 81.108913
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19 2688.0 83.369354 ... 90.532356 89.044730
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20 2816.0 81.674548 ... 83.712490 83.074685
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21 2944.0 82.373605 ... 83.060049 81.967162
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22 3072.0 82.062468 ... 89.451983 87.787755
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23 3200.0 79.701121 ... 88.765601 95.880147
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24 3328.0 83.323259 ... 83.808259 83.034941
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25 3456.0 82.688790 ... 84.597660 87.442050
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26 3584.0 86.291162 ... 97.416461 98.483450
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27 3712.0 82.152425 ... 83.526206 87.629253
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28 3840.0 81.019778 ... 88.544438 90.352941
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29 3968.0 87.976885 ... 92.652949 85.242012
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30 4096.0 93.271527 ... 87.211002 84.573239
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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 16.811 seconds)
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**Total running time of the script:** ( 6 minutes 35.059 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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