[GH-PAGES] Updated website
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@@ -458,37 +458,37 @@ 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 2.978909
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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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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 ... 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 37.971025 ... 40.140799 40.140799
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6 1024.0 49.932191 ... 53.773130 52.428801
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7 1152.0 44.566925 ... 47.396572 47.396572
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7 1152.0 44.566925 ... 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 68.147202
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9 1408.0 64.138541 ... 69.009825 69.009825
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10 1536.0 79.526831 ... 80.430545 80.430545
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11 1664.0 62.929456 ... 63.372618 62.929456
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12 1792.0 72.983276 ... 63.142831 63.142831
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13 1920.0 69.120002 ... 71.626943 70.892307
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14 2048.0 73.908442 ... 78.398206 78.033565
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15 2176.0 83.155572 ... 87.115360 86.367588
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16 2304.0 68.251065 ... 77.307030 77.307030
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17 2432.0 71.125224 ... 75.522751 75.320281
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18 2560.0 77.833728 ... 82.125311 81.715711
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19 2688.0 82.106182 ... 90.966561 90.102270
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20 2816.0 80.026067 ... 79.806423 83.392363
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21 2944.0 81.166173 ... 83.337844 83.060049
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22 3072.0 80.316458 ... 88.750943 87.246694
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23 3200.0 79.651524 ... 96.168294 96.676741
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24 3328.0 83.034941 ... 85.602017 82.843841
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25 3456.0 79.430113 ... 92.033756 84.508982
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26 3584.0 84.905939 ... 88.236146 94.548254
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27 3712.0 85.455380 ... 85.565182 84.946722
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28 3840.0 84.744825 ... 92.895423 85.533390
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29 3968.0 91.472214 ... 84.856701 92.093539
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30 4096.0 86.591209 ... 94.121827 86.035284
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11 1664.0 62.929456 ... 62.929456 62.929456
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12 1792.0 72.512412 ... 63.142831 62.790080
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13 1920.0 69.120002 ... 71.626943 71.257735
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14 2048.0 73.262953 ... 78.033565 77.672296
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15 2176.0 83.155572 ... 87.115360 86.739860
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16 2304.0 68.446623 ... 77.810656 77.057651
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17 2432.0 71.125224 ... 75.320281 75.118889
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18 2560.0 77.833728 ... 81.920002 82.125311
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19 2688.0 83.552988 ... 90.102270 90.316801
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20 2816.0 79.879498 ... 84.197315 83.552120
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21 2944.0 78.854483 ... 82.509987 83.617504
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22 3072.0 82.420822 ... 89.593522 89.877939
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23 3200.0 84.432717 ... 96.385543 95.096582
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24 3328.0 82.275764 ... 84.003845 84.695641
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25 3456.0 82.099354 ... 91.407671 91.824110
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26 3584.0 82.377818 ... 91.380335 93.370085
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27 3712.0 84.730571 ... 89.594031 83.876864
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28 3840.0 84.615146 ... 92.545605 85.663823
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29 3968.0 90.859224 ... 85.932350 86.726322
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30 4096.0 93.825748 ... 86.037005 88.475759
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[31 rows x 5 columns]
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@@ -498,7 +498,7 @@ 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 11.287 seconds)
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**Total running time of the script:** ( 6 minutes 4.629 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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