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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
- cea37d6d 409600 1.097392e+07 9.221097e+02 4.521529e+01 7.930143e+04 7.330044e+07 86
- 617e5fe6 3686400 2.953730e+08 1.884969e+04 7.370619e+02 2.111165e+06 3.985565e+10 112
- afdd228b 1638400 8.758624e+07 5.940712e+03 2.434960e+02 2.376285e+05 1.414054e+09 40
- ####################
- # 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
- 617e5fe6 3686400 2.953730e+08 5.366740e+03 9.457424e+01 1.556354e+05 8.355143e+08 29
- cea37d6d 409600 1.097392e+07 2.003232e+03 2.738589e+01 5.809372e+04 1.163969e+08 29
- afdd228b 1638400 8.758624e+07 3.522008e+03 5.701992e+01 1.021382e+05 3.598259e+08 29
- ####################
- # COMB_3
- # 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 (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 8.758624e+07 3.775579e+03 6.170997e+01 1.094918e+05 4.135053e+08 29
- cea37d6d 409600 1.097392e+07 2.237869e+03 3.535637e+01 6.489820e+04 1.452699e+08 29
- 617e5fe6 3686400 2.953730e+08 5.557011e+03 6.001156e+01 1.611533e+05 8.956353e+08 29
- ####################
- # COMB_2
- # 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 (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
- 617e5fe6 3686400 2.953730e+08 5.500099e+03 6.565775e+01 1.595029e+05 8.774066e+08 29
- cea37d6d 409600 1.097392e+07 2.220120e+03 2.867670e+01 6.438348e+04 1.429629e+08 29
- afdd228b 1638400 8.758624e+07 3.742877e+03 5.898784e+01 1.085434e+05 4.063656e+08 29
|
