################## # 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 f2ff9ae5 34480152 0.000000e+00 4.419323e+01 9.394629e+00 1.825180e+04 8.430572e+05 413 fb4b8624 4427800 0.000000e+00 1.267467e+01 2.411186e+00 5.754301e+03 7.557335e+04 454 4af260f6 14678040 0.000000e+00 2.442142e+01 5.135780e+00 1.394463e+04 3.556084e+05 571 #################### # 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 f2ff9ae5 34480152 0.000000e+00 3.910144e+01 6.371108e+00 1.329449e+03 5.336347e+04 34 fb4b8624 4427800 0.000000e+00 3.998483e+01 8.150933e+00 2.519044e+03 1.049091e+05 63 4af260f6 14678040 0.000000e+00 3.398450e+01 5.156207e+00 8.156280e+02 2.835679e+04 24 #################### # 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 f2ff9ae5 34480152 0.000000e+00 3.173112e+01 3.816078e+00 7.615470e+02 2.451424e+04 24 fb4b8624 4427800 0.000000e+00 2.860497e+01 5.248990e+00 1.029779e+03 3.044867e+04 36 4af260f6 14678040 0.000000e+00 3.652883e+01 8.229435e+00 1.716855e+03 6.589771e+04 47 #################### # 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 f2ff9ae5 34480152 0.000000e+00 3.719045e+01 7.851419e+00 2.566141e+03 9.968943e+04 69 fb4b8624 4427800 0.000000e+00 4.509905e+01 6.110617e+00 9.470800e+02 4.349654e+04 21 4af260f6 14678040 0.000000e+00 2.634116e+01 3.746211e+00 6.479926e+03 1.741412e+05 246