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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
- 492beed5 33177600 7.077888e+09 3.328725e+05 1.185902e+04 2.563119e+07 8.542747e+12 77
- 0b0b0ce8 3686400 2.621440e+08 1.421718e+04 3.409134e+02 9.098993e+05 1.294364e+10 64
- 4220e23d 14745600 2.097152e+09 1.008105e+05 2.361630e+03 8.064841e+06 8.134670e+11 80
- ####################
- # 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
- 492beed5 33177600 7.077888e+09 1.123499e+04 6.785566e+01 1.190909e+06 1.338033e+10 106
- 0b0b0ce8 3686400 2.621440e+08 6.738679e+02 4.393713e+01 6.873452e+04 4.651489e+07 102
- 4220e23d 14745600 2.097152e+09 5.557425e+03 3.241733e+02 5.835297e+05 3.253957e+09 105
- ####################
- # 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
- 492beed5 33177600 7.077888e+09 1.123077e+04 9.504466e+01 1.179231e+06 1.324463e+10 105
- 0b0b0ce8 3686400 2.621440e+08 6.672056e+02 3.376608e+01 6.805497e+04 4.552295e+07 102
- 4220e23d 14745600 2.097152e+09 5.553764e+03 3.500896e+02 5.831453e+05 3.251521e+09 105
- ####################
- # 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
- 492beed5 33177600 7.077888e+09 1.124174e+04 2.629960e+01 1.180383e+06 1.326963e+10 105
- 0b0b0ce8 3686400 2.621440e+08 6.002221e+02 2.259043e+01 6.242310e+04 3.752080e+07 104
- 4220e23d 14745600 2.097152e+09 5.577722e+03 1.615194e+02 5.912385e+05 3.300529e+09 106
|
