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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
- afdd228b 3276800 0.000000e+00 7.065042e+04 7.118479e+03 1.271707e+06 9.075877e+10 18
- 617e5fe6 7372800 0.000000e+00 2.321971e+05 3.386520e+04 2.554168e+06 6.056858e+11 11
- cea37d6d 819200 0.000000e+00 8.644872e+03 1.175676e+03 4.581782e+05 4.034149e+09 53
- ####################
- # 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
- afdd228b 3276800 0.000000e+00 3.469534e+04 1.243993e+03 9.714695e+05 3.374879e+10 28
- 617e5fe6 7372800 0.000000e+00 8.533007e+04 9.757927e+03 1.194621e+06 1.032701e+11 14
- cea37d6d 819200 0.000000e+00 1.145973e+04 6.017234e+02 1.145973e+05 1.316874e+09 10
- ####################
- # COMB_0
- # 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 (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
- afdd228b 3276800 0.000000e+00 3.498011e+04 2.179531e+03 6.996022e+05 2.456717e+10 20
- 617e5fe6 7372800 0.000000e+00 8.442764e+04 6.770170e+03 1.350842e+06 1.147818e+11 16
- cea37d6d 819200 0.000000e+00 1.080764e+04 2.151492e+02 1.188840e+05 1.285365e+09 11
- ####################
- # 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
- afdd228b 3276800 0.000000e+00 3.506064e+04 2.956747e+03 6.310915e+05 2.228383e+10 18
- 617e5fe6 7372800 0.000000e+00 8.151052e+04 4.250155e+02 1.059637e+06 8.637388e+10 13
- cea37d6d 819200 0.000000e+00 1.153062e+04 1.200141e+03 1.153062e+05 1.343956e+09 10
|
