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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
- 2c1922b7 819200 3.287040e+07 1.868713e+03 9.872163e+01 2.535843e+06 4.751987e+09 1357
- ff82dda0 7372800 8.856576e+08 4.564676e+04 7.031596e+02 5.687586e+07 2.596815e+12 1246
- d39bff17 3276800 2.625536e+08 1.417018e+04 5.255501e+02 8.232874e+06 1.168218e+11 581
- ####################
- # 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
- 2c1922b7 819200 3.287040e+07 6.829247e+02 7.632991e+01 1.420483e+05 9.822018e+07 208
- ff82dda0 7372800 8.856576e+08 6.393638e+03 3.362739e+02 3.650767e+06 2.340625e+10 571
- d39bff17 3276800 2.625536e+08 2.602204e+03 1.876810e+02 6.895839e+05 1.803772e+09 265
- ####################
- # 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
- 2c1922b7 819200 3.287040e+07 6.842707e+02 6.860830e+01 1.211159e+05 8.370922e+07 177
- ff82dda0 7372800 8.856576e+08 6.416842e+03 2.746569e+02 2.951747e+06 1.897560e+10 460
- d39bff17 3276800 2.625536e+08 2.601751e+03 2.008905e+02 6.114115e+05 1.600224e+09 235
- ####################
- # 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
- 2c1922b7 819200 3.287040e+07 6.827700e+02 7.214633e+01 1.297263e+05 8.956219e+07 190
- ff82dda0 7372800 8.856576e+08 6.409443e+03 3.434222e+02 3.243178e+06 2.084664e+10 506
- d39bff17 3276800 2.625536e+08 2.604891e+03 2.068197e+02 6.069396e+05 1.590978e+09 233
|
