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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 3276800 0.000000e+00 1.615269e+04 4.099119e+02 4.748890e+06 7.675673e+10 294
- ff82dda0 7372800 0.000000e+00 5.118532e+04 6.422962e+02 1.530441e+07 7.834845e+11 299
- 2c1922b7 819200 0.000000e+00 2.296074e+03 7.445272e+01 1.021753e+06 2.348487e+09 445
- ####################
- # 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
- d39bff17 3276800 0.000000e+00 2.740712e+03 2.663471e+02 5.755494e+05 1.592313e+09 210
- ff82dda0 7372800 0.000000e+00 6.504044e+03 4.912781e+02 1.385361e+06 9.061859e+09 213
- 2c1922b7 819200 0.000000e+00 6.801212e+02 1.149855e+02 1.129001e+05 7.898057e+07 166
- ####################
- # 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
- d39bff17 3276800 0.000000e+00 2.716114e+03 2.688407e+02 4.237138e+05 1.162130e+09 156
- ff82dda0 7372800 0.000000e+00 6.512491e+03 5.367987e+02 8.270864e+05 5.422988e+09 127
- 2c1922b7 819200 0.000000e+00 7.284912e+02 1.021807e+02 1.049027e+05 7.792421e+07 144
- ####################
- # 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 3276800 0.000000e+00 2.294336e+03 5.071880e+02 4.909878e+05 1.181540e+09 214
- ff82dda0 7372800 0.000000e+00 6.469485e+03 5.370376e+02 7.698688e+05 5.014976e+09 119
- 2c1922b7 819200 0.000000e+00 7.112055e+02 1.136474e+02 1.002800e+05 7.314078e+07 141
|
