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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
- 24c84a50 22118400 0.000000e+00 1.687897e+05 8.023245e+03 3.110794e+08 5.262564e+13 1843
- f0ac7beb 9830400 0.000000e+00 5.125521e+04 2.656019e+03 7.375625e+07 3.790543e+12 1439
- d46431bb 2457600 0.000000e+00 6.821106e+03 3.878220e+02 1.100926e+07 7.533811e+10 1614
- ####################
- # 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 22118400 0.000000e+00 5.852261e+03 2.067645e+02 2.783335e+07 1.630914e+11 4756
- f0ac7beb 9830400 0.000000e+00 1.831142e+03 6.447275e+01 9.274735e+06 1.700441e+10 5065
- d46431bb 2457600 0.000000e+00 2.556618e+02 1.838263e+01 1.252232e+06 3.218030e+08 4898
- ####################
- # COMB_0
- # 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 (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 22118400 0.000000e+00 5.846675e+03 2.141855e+02 2.732736e+07 1.599886e+11 4674
- f0ac7beb 9830400 0.000000e+00 1.834114e+03 5.380375e+01 9.566740e+06 1.756159e+10 5216
- d46431bb 2457600 0.000000e+00 2.610266e+02 2.020042e+01 1.246402e+06 3.272925e+08 4775
- ####################
- # 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
- 24c84a50 22118400 0.000000e+00 5.840318e+03 1.756302e+02 2.921911e+07 1.708032e+11 5003
- f0ac7beb 9830400 0.000000e+00 1.840833e+03 4.879997e+01 9.542881e+06 1.757920e+10 5184
- d46431bb 2457600 0.000000e+00 2.617920e+02 1.853601e+01 1.281472e+06 3.371609e+08 4895
|
