[GH-PAGES] Updated website
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@@ -459,9 +459,9 @@ 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 2.849391 ... 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 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 ... 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 ... 41.321411 39.025776
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@@ -470,26 +470,26 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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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 79.526831 ... 80.430545 78.643199
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11 1664.0 62.929456 ... 63.372618 62.061463
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12 1792.0 72.983276 ... 63.499573 63.142831
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13 1920.0 69.467336 ... 71.626943 70.892307
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14 2048.0 73.262953 ... 78.033565 76.959706
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15 2176.0 83.155572 ... 87.115360 85.632545
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16 2304.0 68.251065 ... 78.064941 76.809875
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17 2432.0 71.305746 ... 75.522751 74.521127
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18 2560.0 77.833728 ... 81.920002 81.310171
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19 2688.0 84.108772 ... 90.966561 90.102270
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20 2816.0 79.443003 ... 84.687779 82.602666
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21 2944.0 82.646820 ... 83.337844 82.921853
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22 3072.0 82.301023 ... 89.310890 88.750943
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23 3200.0 84.768213 ... 96.385543 94.674553
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24 3328.0 83.034941 ... 83.808259 86.011103
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25 3456.0 82.519518 ... 90.281712 88.986281
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26 3584.0 83.954614 ... 88.496679 95.451583
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27 3712.0 84.159518 ... 87.552452 86.942857
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28 3840.0 85.136259 ... 91.625518 86.332554
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29 3968.0 91.816356 ... 85.091543 91.130650
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30 4096.0 86.508362 ... 88.098281 92.563952
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11 1664.0 63.372618 ... 63.372618 62.492442
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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 73.262953 ... 78.033565 77.314362
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15 2176.0 83.155572 ... 87.494120 85.632545
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16 2304.0 68.251065 ... 78.320893 77.057651
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17 2432.0 71.305746 ... 75.522751 75.118889
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18 2560.0 77.833728 ... 82.125311 80.908642
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19 2688.0 83.922689 ... 89.676257 89.254248
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20 2816.0 81.674548 ... 84.523664 82.602666
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21 2944.0 82.373605 ... 83.337844 82.921853
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22 3072.0 82.301023 ... 89.170242 88.612060
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23 3200.0 84.768213 ... 96.530922 94.955488
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24 3328.0 83.808259 ... 85.602017 85.602017
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25 3456.0 81.026701 ... 87.536988 86.783176
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26 3584.0 87.381330 ... 98.375705 96.996106
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27 3712.0 82.355598 ... 89.674457 87.475786
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28 3840.0 84.100380 ... 93.090912 86.943395
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29 3968.0 92.652949 ... 85.932350 91.266964
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30 4096.0 86.396989 ... 89.181212 82.342167
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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:** ( 6 minutes 5.171 seconds)
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**Total running time of the script:** ( 6 minutes 3.569 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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