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- ##################
- # Performance Model Version
- 45
- ####################
- # COMBs
- # number of combinations
- 4
- ####################
- # COMB_0
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 0
- ####################
- # DEV_0
- # device id
- 0
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cpu0_impl0 (Comb0)
- # number of entries
- 3
- # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx
- 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0
- # a b c
- nan nan nan
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- fb4b8624 4427800 0.000000e+00 1.161593e+01 2.312881e+00 1.684310e+04 2.034051e+05 1450
- 4af260f6 14678040 0.000000e+00 2.793439e+01 6.208645e+00 2.807406e+04 8.229715e+05 1005
- f2ff9ae5 34480152 0.000000e+00 5.388292e+01 1.191766e+01 4.930288e+04 2.786541e+06 915
- ####################
- # COMB_1
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 1
- ####################
- # DEV_0
- # device id
- 0
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda0_impl0 (Comb1)
- # number of entries
- 3
- # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx
- 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0
- # a b c
- nan nan nan
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- fb4b8624 4427800 0.000000e+00 3.349897e+01 6.495369e+00 7.939257e+03 2.759560e+05 237
- 4af260f6 14678040 0.000000e+00 3.814493e+01 8.460348e+00 1.609716e+04 6.442306e+05 422
- f2ff9ae5 34480152 0.000000e+00 3.894616e+01 8.022125e+00 1.339748e+04 5.439182e+05 344
- ####################
- # COMB_2
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 1
- ####################
- # DEV_0
- # device id
- 1
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda1_impl0 (Comb2)
- # number of entries
- 3
- # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx
- 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0
- # a b c
- nan nan nan
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- fb4b8624 4427800 0.000000e+00 4.505725e+01 1.044174e+01 7.209160e+02 3.422697e+04 16
- 4af260f6 14678040 0.000000e+00 3.820932e+01 8.787776e+00 1.138638e+04 4.580788e+05 298
- f2ff9ae5 34480152 0.000000e+00 4.714002e+01 1.060923e+01 1.343491e+04 6.654002e+05 285
- ####################
- # COMB_3
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3)
- 1
- ####################
- # DEV_0
- # device id
- 2
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda2_impl0 (Comb3)
- # number of entries
- 3
- # sumlnx sumlnx2 sumlny sumlnxlny alpha beta n minx maxx
- 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 nan nan 0 0 0
- # a b c
- nan nan nan
- # not multiple-regression-base
- 0
- # hash size flops mean (us) dev (us) sum sum2 n
- fb4b8624 4427800 0.000000e+00 2.397521e+01 2.109607e+00 5.754050e+02 1.390227e+04 24
- 4af260f6 14678040 0.000000e+00 3.827520e+01 8.943097e+00 9.453975e+03 3.816076e+05 247
- f2ff9ae5 34480152 0.000000e+00 5.567087e+01 1.159966e+01 8.127947e+03 4.721345e+05 146
|
