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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
- f0ac7beb 4915200 0.000000e+00 2.645658e+04 4.968429e+02 5.820449e+07 1.540435e+12 2200
- 24c84a50 11059200 0.000000e+00 8.756135e+04 9.752924e+02 1.866808e+08 1.634805e+13 2132
- d46431bb 1228800 0.000000e+00 3.234444e+03 8.877025e+01 1.325799e+07 4.291452e+10 4099
- ####################
- # 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
- f0ac7beb 4915200 0.000000e+00 8.760921e+02 3.574580e+01 7.074444e+06 6.208182e+09 8075
- 24c84a50 11059200 0.000000e+00 2.988744e+03 8.136061e+01 2.363499e+07 7.069126e+10 7908
- d46431bb 1228800 0.000000e+00 1.911930e+02 1.434147e+01 1.248108e+06 2.399722e+08 6528
- ####################
- # 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
- f0ac7beb 4915200 0.000000e+00 9.198175e+02 4.677043e+01 6.931745e+06 6.392425e+09 7536
- 24c84a50 11059200 0.000000e+00 3.016176e+03 6.737054e+01 2.311597e+07 6.975663e+10 7664
- d46431bb 1228800 0.000000e+00 1.910500e+02 1.400155e+01 1.317099e+06 2.529832e+08 6894
- ####################
- # 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
- f0ac7beb 4915200 0.000000e+00 9.143628e+02 4.685332e+01 6.720566e+06 6.161171e+09 7350
- 24c84a50 11059200 0.000000e+00 3.002393e+03 6.861698e+01 2.339765e+07 7.028562e+10 7793
- d46431bb 1228800 0.000000e+00 1.898967e+02 1.421585e+01 1.327568e+06 2.535136e+08 6991
|
