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- ##################
- # Performance Model Version
- 45
- ####################
- # COMBs
- # number of combinations
- 4
- ####################
- # COMB_3
- # 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 (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
- d39bff17 3276800 0.000000e+00 1.377909e+04 1.008911e+03 6.145473e+06 8.513300e+10 446
- ff82dda0 7372800 0.000000e+00 4.298380e+04 1.919778e+03 1.177756e+07 5.072542e+11 274
- 2c1922b7 819200 0.000000e+00 1.936516e+03 1.503574e+02 4.725100e+05 9.205395e+08 244
- ####################
- # COMB_2
- # 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 (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
- d39bff17 3276800 0.000000e+00 2.656425e+03 2.270595e+02 3.320531e+05 8.885184e+08 125
- ff82dda0 7372800 0.000000e+00 6.358340e+03 3.816293e+02 5.023088e+05 3.205356e+09 79
- 2c1922b7 819200 0.000000e+00 3.867923e+02 4.867053e+01 4.564149e+04 1.793330e+07 118
- ####################
- # COMB_1
- # 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 (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
- d39bff17 3276800 0.000000e+00 1.902887e+03 4.574719e+02 4.585957e+05 9.230924e+08 241
- ff82dda0 7372800 0.000000e+00 3.810456e+03 1.334249e+02 3.353201e+05 1.279289e+09 88
- 2c1922b7 819200 0.000000e+00 3.835296e+02 4.543249e+01 2.262825e+04 8.800385e+06 59
- ####################
- # COMB_0
- # 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 (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
- d39bff17 3276800 0.000000e+00 2.657310e+03 2.918518e+02 3.162199e+05 8.504305e+08 119
- ff82dda0 7372800 0.000000e+00 3.819809e+03 1.073068e+02 3.055848e+05 1.168197e+09 80
- 2c1922b7 819200 0.000000e+00 4.020211e+02 5.372009e+01 3.256371e+04 1.332505e+07 81
|
