################## # Performance Model Version 45 #################### # COMBs # number of combinations 9 #################### # COMB_8 # 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 (Comb8) # 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 d46431bb 1228800 0.000000e+00 3.393927e+03 8.566524e+01 3.533078e+06 1.199865e+10 1041 f0ac7beb 4915200 0.000000e+00 2.682238e+04 4.332821e+02 9.951104e+06 2.669820e+11 371 24c84a50 11059200 0.000000e+00 8.930213e+04 1.450773e+03 2.679064e+07 2.393092e+12 300 #################### # COMB_5 # 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 (Comb5) # 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 d46431bb 1228800 0.000000e+00 1.946363e+02 2.537099e+01 6.294539e+05 1.245963e+08 3234 f0ac7beb 4915200 0.000000e+00 9.257288e+02 6.590058e+01 3.791785e+06 3.527953e+09 4096 24c84a50 11059200 0.000000e+00 2.991139e+03 1.645886e+02 1.221282e+07 3.664085e+10 4083 #################### # COMB_0 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 4 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda4_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 d46431bb 1228800 0.000000e+00 1.954243e+02 2.831383e+01 5.661443e+05 1.129608e+08 2897 f0ac7beb 4915200 0.000000e+00 9.376794e+02 7.341921e+01 3.415966e+06 3.222718e+09 3643 24c84a50 11059200 0.000000e+00 2.995872e+03 1.614697e+02 1.133938e+07 3.407000e+10 3785 #################### # COMB_1 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 6 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda6_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 d46431bb 1228800 0.000000e+00 1.867261e+02 2.556099e+01 5.342234e+05 1.016227e+08 2861 f0ac7beb 4915200 0.000000e+00 8.996740e+02 6.639270e+01 3.427758e+06 3.100659e+09 3810 24c84a50 11059200 0.000000e+00 2.987519e+03 1.530428e+02 1.113747e+07 3.336072e+10 3728 #################### # COMB_3 # 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 (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 d46431bb 1228800 0.000000e+00 1.927028e+02 2.478568e+01 6.783137e+05 1.328754e+08 3520 f0ac7beb 4915200 0.000000e+00 9.234475e+02 6.432680e+01 3.846159e+06 3.568960e+09 4165 24c84a50 11059200 0.000000e+00 2.982449e+03 1.542480e+02 1.210278e+07 3.619247e+10 4058 #################### # COMB_2 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 5 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda5_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 d46431bb 1228800 0.000000e+00 1.868734e+02 2.558187e+01 5.049318e+05 9.612659e+07 2702 f0ac7beb 4915200 0.000000e+00 9.407115e+02 6.874274e+01 3.317889e+06 3.137844e+09 3527 24c84a50 11059200 0.000000e+00 2.972987e+03 1.569773e+02 1.177600e+07 3.510750e+10 3961 #################### # COMB_6 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 3 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda3_impl0 (Comb6) # 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 d46431bb 1228800 0.000000e+00 1.924732e+02 2.459364e+01 6.245755e+05 1.221768e+08 3245 f0ac7beb 4915200 0.000000e+00 9.173887e+02 7.039530e+01 3.781476e+06 3.489510e+09 4122 24c84a50 11059200 0.000000e+00 3.001859e+03 1.612679e+02 1.156916e+07 3.482922e+10 3854 #################### # COMB_4 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 7 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda7_impl0 (Comb4) # 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 d46431bb 1228800 0.000000e+00 1.877972e+02 2.764994e+01 5.324050e+05 1.021516e+08 2835 f0ac7beb 4915200 0.000000e+00 9.245688e+02 6.946750e+01 3.363581e+06 3.127419e+09 3638 24c84a50 11059200 0.000000e+00 3.005524e+03 1.690713e+02 1.154422e+07 3.480621e+10 3841 #################### # COMB_7 # 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 (Comb7) # 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 d46431bb 1228800 0.000000e+00 1.865351e+02 2.381101e+01 6.651841e+05 1.261020e+08 3566 f0ac7beb 4915200 0.000000e+00 9.257403e+02 6.896157e+01 3.669635e+06 3.415980e+09 3964 24c84a50 11059200 0.000000e+00 3.007743e+03 1.477912e+02 1.238889e+07 3.735258e+10 4119