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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 1.291871e+01 2.707056e+00 1.452063e+04 1.958246e+05 1124
- 4af260f6 14678040 0.000000e+00 2.737328e+01 5.740626e+00 2.241872e+04 6.406639e+05 819
- f2ff9ae5 34480152 0.000000e+00 4.727593e+01 1.006422e+01 4.179193e+04 2.065291e+06 884
- ####################
- # 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 4.529760e+01 1.106616e+01 3.940891e+03 1.891669e+05 87
- 4af260f6 14678040 0.000000e+00 5.186998e+01 9.163546e+00 2.386019e+03 1.276254e+05 46
- f2ff9ae5 34480152 0.000000e+00 5.555996e+01 1.123960e+01 2.777998e+03 1.606619e+05 50
- ####################
- # 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 4.174505e+01 7.717897e+00 1.711547e+03 7.389082e+04 41
- 4af260f6 14678040 0.000000e+00 4.338701e+01 9.950636e+00 8.677401e+03 3.962895e+05 200
- f2ff9ae5 34480152 0.000000e+00 5.523574e+01 1.243105e+01 2.154194e+03 1.250152e+05 39
- ####################
- # 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 5.145250e+01 1.035300e+01 1.955195e+03 1.046727e+05 38
- 4af260f6 14678040 0.000000e+00 4.717138e+01 8.365012e+00 2.217055e+03 1.078703e+05 47
- f2ff9ae5 34480152 0.000000e+00 4.374296e+01 8.852326e+00 3.455694e+03 1.573530e+05 79
|
