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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
- afdd228b 1638400 0.000000e+00 4.182946e+04 4.195402e+03 1.171225e+06 4.948453e+10 28
- 617e5fe6 3686400 0.000000e+00 1.431791e+05 1.961610e+04 1.431791e+06 2.088506e+11 10
- cea37d6d 409600 0.000000e+00 4.839229e+03 3.061560e+02 1.258200e+05 6.113086e+08 26
- ####################
- # 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
- afdd228b 1638400 0.000000e+00 2.565619e+04 2.729977e+03 4.618114e+05 1.198247e+10 18
- 617e5fe6 3686400 0.000000e+00 5.517976e+04 5.023576e+03 8.828762e+05 4.912068e+10 16
- cea37d6d 409600 0.000000e+00 9.325377e+03 4.741281e+02 9.325377e+04 8.718745e+08 10
- ####################
- # COMB_1
- # 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 (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
- afdd228b 1638400 0.000000e+00 2.512124e+04 2.223761e+03 4.773036e+05 1.208442e+10 19
- 617e5fe6 3686400 0.000000e+00 5.116041e+04 1.272422e+03 7.674062e+05 3.928511e+10 15
- cea37d6d 409600 0.000000e+00 9.353760e+03 7.152342e+02 9.353760e+04 8.800438e+08 10
- ####################
- # COMB_0
- # 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 (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
- afdd228b 1638400 0.000000e+00 2.814234e+04 3.880171e+03 5.065622e+05 1.452685e+10 18
- 617e5fe6 3686400 0.000000e+00 5.467956e+04 6.741916e+03 8.201934e+05 4.552961e+10 15
- cea37d6d 409600 0.000000e+00 1.004502e+04 9.839619e+02 1.004502e+05 1.018706e+09 10
|
