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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
- 617e5fe6 3686400 2.953730e+08 7.593370e+04 4.030251e+03 2.353945e+06 1.792473e+11 31
- afdd228b 1638400 8.758624e+07 2.346245e+04 1.988237e+03 1.032348e+06 2.439534e+10 44
- cea37d6d 409600 1.097392e+07 3.401100e+03 3.819888e+02 1.564506e+05 5.388163e+08 46
- ####################
- # 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
- 617e5fe6 3686400 2.953730e+08 4.425357e+04 2.763302e+03 7.523107e+05 3.342224e+10 17
- afdd228b 1638400 8.758624e+07 2.425311e+04 2.094515e+03 2.910373e+05 7.111204e+09 12
- cea37d6d 409600 1.097392e+07 1.130795e+04 5.745206e+02 1.130795e+05 1.281997e+09 10
- ####################
- # 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
- 617e5fe6 3686400 2.953730e+08 4.555777e+04 5.907293e+03 7.744821e+05 3.587692e+10 17
- afdd228b 1638400 8.758624e+07 2.509024e+04 3.469720e+03 2.509024e+05 6.415590e+09 10
- cea37d6d 409600 1.097392e+07 1.082278e+04 2.477308e+02 1.082278e+05 1.171939e+09 10
- ####################
- # 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
- 617e5fe6 3686400 2.953730e+08 4.828333e+04 3.379151e+03 5.311166e+05 2.576968e+10 11
- afdd228b 1638400 8.758624e+07 2.737149e+04 3.217773e+03 2.737149e+05 7.595526e+09 10
- cea37d6d 409600 1.097392e+07 1.143954e+04 1.654563e+02 1.143954e+05 1.308904e+09 10
|
