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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
- d39bff17 6553600 0.000000e+00 2.758103e+04 7.024890e+02 7.033162e+06 1.941076e+11 255
- ff82dda0 14745600 0.000000e+00 9.143755e+04 1.725750e+03 1.234407e+07 1.129114e+12 135
- 2c1922b7 1638400 0.000000e+00 3.516018e+03 1.528455e+02 1.613852e+06 5.685057e+09 459
- ####################
- # COMB_2
- # 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 (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
- d39bff17 6553600 0.000000e+00 2.131008e+03 3.294125e+02 6.755295e+05 1.473957e+09 317
- ff82dda0 14745600 0.000000e+00 7.209283e+03 1.090675e+03 1.564414e+06 1.153644e+10 217
- 2c1922b7 1638400 0.000000e+00 6.237527e+02 1.148972e+02 1.210080e+05 7.804013e+07 194
- ####################
- # COMB_0
- # 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 (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
- d39bff17 6553600 0.000000e+00 2.163459e+03 3.374464e+02 5.538454e+05 1.227372e+09 256
- ff82dda0 14745600 0.000000e+00 6.895326e+03 1.111793e+03 1.234263e+06 8.731908e+09 179
- 2c1922b7 1638400 0.000000e+00 6.290993e+02 1.019490e+02 1.333690e+05 8.610581e+07 212
- ####################
- # 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
- d39bff17 6553600 0.000000e+00 2.119354e+03 3.243594e+02 5.912998e+05 1.282527e+09 279
- ff82dda0 14745600 0.000000e+00 6.998019e+03 1.239620e+03 1.070697e+06 7.727865e+09 153
- 2c1922b7 1638400 0.000000e+00 6.140937e+02 1.075567e+02 1.430838e+05 9.056234e+07 233
|
