################## # Performance Model Version 44 #################### # COMBs # number of combinations 5 #################### # COMB_0 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4) 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 # hash size flops mean (us) dev (us) sum sum2 n ff82dda0 7372800 8.856576e+08 1.775772e+04 3.736007e+03 2.386637e+07 4.425714e+11 1344 d39bff17 3276800 2.625536e+08 5.276862e+03 9.789431e+02 7.070995e+06 3.859682e+10 1340 2c1922b7 819200 3.287040e+07 7.675336e+02 1.464194e+02 2.842177e+06 2.260854e+09 3703 #################### # COMB_2 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4) 1 #################### # DEV_0 # device id 3 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda3_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 # hash size flops mean (us) dev (us) sum sum2 n ff82dda0 7372800 8.856576e+08 2.018325e+03 2.870643e+02 1.687320e+06 3.474450e+09 836 d39bff17 3276800 2.625536e+08 1.179394e+03 1.705358e+02 3.538181e+05 4.260157e+08 300 2c1922b7 819200 3.287040e+07 4.644748e+02 7.687001e+01 3.297771e+04 1.573685e+07 71 #################### # COMB_1 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4) 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 # hash size flops mean (us) dev (us) sum sum2 n ff82dda0 7372800 8.856576e+08 1.972468e+03 2.888901e+02 1.510910e+06 3.044151e+09 766 d39bff17 3276800 2.625536e+08 1.215766e+03 1.649819e+02 2.869207e+05 3.552521e+08 236 2c1922b7 819200 3.287040e+07 4.764697e+02 7.471348e+01 4.621756e+04 2.256273e+07 97 #################### # COMB_4 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4) 1 #################### # DEV_0 # device id 1 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda1_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 # hash size flops mean (us) dev (us) sum sum2 n ff82dda0 7372800 8.856576e+08 2.005118e+03 2.787124e+02 1.836689e+06 3.753933e+09 916 d39bff17 3276800 2.625536e+08 1.227664e+03 1.874122e+02 2.970946e+05 3.732321e+08 242 2c1922b7 819200 3.287040e+07 4.209987e+02 9.547071e+01 6.441281e+04 2.851225e+07 153 #################### # COMB_3 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4) 1 #################### # DEV_0 # device id 2 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda2_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 # hash size flops mean (us) dev (us) sum sum2 n ff82dda0 7372800 8.856576e+08 2.051755e+03 2.742098e+02 1.811700e+06 3.783559e+09 883 d39bff17 3276800 2.625536e+08 1.153240e+03 1.913332e+02 3.194475e+05 3.785401e+08 277 2c1922b7 819200 3.287040e+07 4.950127e+02 6.747714e+01 5.445140e+04 2.745498e+07 110