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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
- 6d78e48f 4461600 0.000000e+00 6.670318e+03 3.279077e+02 6.103341e+06 4.080961e+10 915
- 8ec75d42 14753312 0.000000e+00 2.178007e+04 1.559694e+03 1.008417e+07 2.207603e+11 463
- 49ec0825 34613280 0.000000e+00 5.101465e+04 2.613713e+03 2.443602e+07 1.249867e+12 479
- ####################
- # 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
- 6d78e48f 4461600 0.000000e+00 1.028619e+03 1.201323e+02 5.626547e+05 5.866515e+08 547
- 8ec75d42 14753312 0.000000e+00 1.871093e+03 3.437894e+02 1.981488e+06 3.832713e+09 1059
- 49ec0825 34613280 0.000000e+00 5.018828e+03 7.664203e+02 4.672528e+06 2.399748e+10 931
- ####################
- # 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
- 6d78e48f 4461600 0.000000e+00 1.024201e+03 1.096599e+02 6.452464e+05 6.684377e+08 630
- 8ec75d42 14753312 0.000000e+00 1.877457e+03 3.608958e+02 1.907496e+06 3.713572e+09 1016
- 49ec0825 34613280 0.000000e+00 5.018101e+03 7.255196e+02 5.314169e+06 2.722447e+10 1059
- ####################
- # 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
- 6d78e48f 4461600 0.000000e+00 1.010004e+03 1.090743e+02 5.383321e+05 5.500588e+08 533
- 8ec75d42 14753312 0.000000e+00 1.986058e+03 3.264552e+02 1.288952e+06 2.629100e+09 649
- 49ec0825 34613280 0.000000e+00 5.064765e+03 7.492118e+02 4.948276e+06 2.561026e+10 977
|
