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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 2.762618e+04 9.983022e+02 6.575032e+06 1.818802e+11 238
- ff82dda0 14745600 0.000000e+00 9.068591e+04 1.985325e+03 1.324014e+07 1.201270e+12 146
- 2c1922b7 1638400 0.000000e+00 3.579286e+03 2.361748e+02 1.449611e+06 5.211162e+09 405
- ####################
- # 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 2.106536e+03 3.670134e+02 5.856171e+05 1.271070e+09 278
- ff82dda0 14745600 0.000000e+00 7.299043e+03 1.073594e+03 1.284632e+06 9.579441e+09 176
- 2c1922b7 1638400 0.000000e+00 6.166979e+02 1.186269e+02 1.362902e+05 8.715990e+07 221
- ####################
- # 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 2.072463e+03 3.421274e+02 6.590431e+05 1.403064e+09 318
- ff82dda0 14745600 0.000000e+00 6.791353e+03 1.183637e+03 1.195278e+06 8.364131e+09 176
- 2c1922b7 1638400 0.000000e+00 6.128580e+02 1.104622e+02 1.378931e+05 8.725430e+07 225
- ####################
- # 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 2.129169e+03 3.327197e+02 5.024838e+05 1.095999e+09 236
- ff82dda0 14745600 0.000000e+00 6.700018e+03 1.125184e+03 1.139003e+06 7.846568e+09 170
- 2c1922b7 1638400 0.000000e+00 6.207819e+02 1.142635e+02 1.440214e+05 9.243491e+07 232
|
