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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 1.373117e+04 2.756172e+02 7.167670e+06 9.846014e+10 522
- ff82dda0 7372800 0.000000e+00 4.545501e+04 7.462378e+02 1.750018e+07 7.956851e+11 385
- 2c1922b7 819200 0.000000e+00 1.798916e+03 8.480081e+01 1.219665e+06 2.198952e+09 678
- ####################
- # COMB_0
- # 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 (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 2.883473e+03 4.679640e+02 2.537456e+05 7.509396e+08 88
- ff82dda0 7372800 0.000000e+00 6.462089e+03 4.136967e+02 5.751259e+05 3.731746e+09 89
- 2c1922b7 819200 0.000000e+00 4.040830e+02 6.411732e+01 3.717564e+04 1.540026e+07 92
- ####################
- # 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
- d39bff17 3276800 0.000000e+00 2.231007e+03 5.378925e+02 3.234960e+05 7.636746e+08 145
- ff82dda0 7372800 0.000000e+00 3.904524e+03 2.515208e+02 4.021660e+05 1.576783e+09 103
- 2c1922b7 819200 0.000000e+00 5.307827e+02 1.276617e+02 5.467062e+04 3.069686e+07 103
- ####################
- # COMB_1
- # 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 (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 1.665736e+03 1.392688e+02 2.881723e+05 4.833744e+08 173
- ff82dda0 7372800 0.000000e+00 3.891632e+03 2.259287e+02 7.199519e+05 2.811230e+09 185
- 2c1922b7 819200 0.000000e+00 5.125766e+02 1.240167e+02 5.587085e+04 3.031453e+07 109
|
