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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
- 24c84a50 11059200 1.769472e+09 8.407559e+04 3.415249e+03 1.399859e+08 1.178881e+13 1665
- f0ac7beb 4915200 5.242880e+08 2.610119e+04 1.422415e+03 4.251883e+07 1.113088e+12 1629
- d46431bb 1228800 6.553600e+07 3.432588e+03 1.640071e+02 9.130685e+06 3.141343e+10 2660
- ####################
- # 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
- 24c84a50 11059200 1.769472e+09 2.795670e+03 5.624760e+01 1.818024e+07 5.084653e+10 6503
- f0ac7beb 4915200 5.242880e+08 8.880682e+02 3.243424e+01 5.760010e+06 5.122105e+09 6486
- d46431bb 1228800 6.553600e+07 2.022322e+02 1.071833e+01 1.116119e+06 2.263493e+08 5519
- ####################
- # 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
- 24c84a50 11059200 1.769472e+09 2.815870e+03 4.694553e+01 1.827781e+07 5.148226e+10 6491
- f0ac7beb 4915200 5.242880e+08 8.961392e+02 3.565427e+01 5.741564e+06 5.153386e+09 6407
- d46431bb 1228800 6.553600e+07 2.020566e+02 9.551669e+00 1.107876e+06 2.243540e+08 5483
- ####################
- # 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
- 24c84a50 11059200 1.769472e+09 2.810209e+03 3.946230e+01 1.806121e+07 5.076578e+10 6427
- f0ac7beb 4915200 5.242880e+08 8.833768e+02 3.092949e+01 5.707497e+06 5.048051e+09 6461
- d46431bb 1228800 6.553600e+07 1.637484e+02 6.969807e+00 1.084015e+06 1.778273e+08 6620
|
