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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 3.789658e+04 4.182352e+03 1.250587e+06 4.797021e+10 33
- 617e5fe6 3686400 0.000000e+00 1.286436e+05 1.271269e+04 2.958803e+06 3.843483e+11 23
- cea37d6d 409600 0.000000e+00 4.236597e+03 2.366692e+02 2.372495e+05 1.008267e+09 56
- ####################
- # 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
- afdd228b 1638400 0.000000e+00 2.864580e+04 3.233071e+03 5.156243e+05 1.495862e+10 18
- 617e5fe6 3686400 0.000000e+00 5.948740e+04 4.910517e+03 1.070773e+06 6.413154e+10 18
- cea37d6d 409600 0.000000e+00 1.060245e+04 4.247968e+02 1.060245e+05 1.125924e+09 10
- ####################
- # 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
- afdd228b 1638400 0.000000e+00 3.046163e+04 4.754796e+03 5.483094e+05 1.710934e+10 18
- 617e5fe6 3686400 0.000000e+00 5.865963e+04 4.672589e+03 1.349171e+06 7.964405e+10 23
- cea37d6d 409600 0.000000e+00 1.042618e+04 1.817032e+02 1.042618e+05 1.087383e+09 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
- 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
- afdd228b 1638400 0.000000e+00 2.939722e+04 4.040622e+03 4.409582e+05 1.320784e+10 15
- 617e5fe6 3686400 0.000000e+00 5.704610e+04 3.429433e+03 1.255014e+06 7.185241e+10 22
- cea37d6d 409600 0.000000e+00 1.049902e+04 4.776188e+02 1.049902e+05 1.104575e+09 10
|
