[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 2.978909 ... 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 ... 16.384000 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 ... 35.389441 34.028308
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5 896.0 39.025776 ... 40.140799 39.025776
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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 ... 47.396572 47.396572
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7 1152.0 44.566925 ... 47.396572 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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11 1664.0 62.492442 ... 63.372618 62.492442
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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 68.776119 ... 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 77.307030
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17 2432.0 71.305746 ... 85.653855 75.320281
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18 2560.0 77.833728 ... 82.747477 81.108913
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19 2688.0 83.186525 ... 90.102270 90.316801
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20 2816.0 80.173175 ... 84.523664 83.712490
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21 2944.0 81.832567 ... 83.198715 81.832567
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22 3072.0 82.420822 ... 89.877939 88.890270
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23 3200.0 84.544253 ... 96.822991 94.955488
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24 3328.0 83.130825 ... 85.196803 84.695641
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25 3456.0 82.015834 ... 91.719645 91.563392
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26 3584.0 87.381330 ... 94.697621 95.451583
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27 3712.0 83.386762 ... 87.246590 87.475786
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28 3840.0 80.197243 ... 89.548180 91.891984
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29 3968.0 88.039362 ... 90.522206 84.328915
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30 4096.0 92.245860 ... 84.149044 89.837839
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16 2304.0 68.251065 ... 78.064941 77.057651
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17 2432.0 71.305746 ... 83.614477 83.366361
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18 2560.0 77.833728 ... 82.747477 81.715711
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19 2688.0 83.922689 ... 90.748936 89.044730
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20 2816.0 82.759409 ... 84.197315 83.712490
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21 2944.0 81.298583 ... 83.899046 80.771529
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22 3072.0 81.825298 ... 89.310890 87.246694
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23 3200.0 81.424937 ... 97.116842 95.096582
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24 3328.0 84.003845 ... 85.908470 84.101981
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25 3456.0 79.118323 ... 85.585527 88.400840
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26 3584.0 87.127323 ... 99.518972 95.756542
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27 3712.0 84.159518 ... 84.658765 87.937800
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28 3840.0 84.615146 ... 89.042358 84.323810
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29 3968.0 92.512459 ... 81.950257 84.915752
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30 4096.0 87.381330 ... 85.489001 90.079009
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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 8.214 seconds)
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**Total running time of the script:** ( 6 minutes 21.317 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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