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@@ -1765,10 +1765,10 @@ to choose the performance model to be displayed. The result looks like:
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@example
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$ starpu_perfmodel_display -s starpu_dlu_lu_model_22
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performance model for cpu
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-# hash size mean dev n
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-880805ba 98304 2.731309e+02 6.010210e+01 1240
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-b50b6605 393216 1.469926e+03 1.088828e+02 1240
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-5c6c3401 1572864 1.125983e+04 3.265296e+03 1240
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+# hash size mean dev n
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+880805ba 98304 2.731309e+02 6.010210e+01 1240
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+b50b6605 393216 1.469926e+03 1.088828e+02 1240
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+5c6c3401 1572864 1.125983e+04 3.265296e+03 1240
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@end example
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Which shows that for the LU 22 kernel with a 1.5MiB matrix, the average
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@@ -2231,17 +2231,17 @@ performance of the 22 kernel:
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@example
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$ starpu_perfmodel_display -s starpu_slu_lu_model_22
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performance model for cpu
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-# hash size mean dev n
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-57618ab0 19660800 2.851069e+05 1.829369e+04 109
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+# hash size mean dev n
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+57618ab0 19660800 2.851069e+05 1.829369e+04 109
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performance model for cuda_0
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-# hash size mean dev n
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-57618ab0 19660800 1.164144e+04 1.556094e+01 315
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+# hash size mean dev n
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+57618ab0 19660800 1.164144e+04 1.556094e+01 315
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performance model for cuda_1
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-# hash size mean dev n
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-57618ab0 19660800 1.164271e+04 1.330628e+01 360
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+# hash size mean dev n
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+57618ab0 19660800 1.164271e+04 1.330628e+01 360
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performance model for cuda_2
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-# hash size mean dev n
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-57618ab0 19660800 1.166730e+04 3.390395e+02 456
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+# hash size mean dev n
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+57618ab0 19660800 1.166730e+04 3.390395e+02 456
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@end example
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We can see that for the given size, over a sample of a few hundreds of
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