################## # Performance Model Version 44 #################### # COMBs # number of combinations 9 #################### # 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 4af260f6 14678040 0.000000e+00 3.246622e+01 6.891153e+00 3.928413e+03 1.332868e+05 121 fb4b8624 4427800 0.000000e+00 1.139753e+01 2.243693e+00 2.644226e+03 3.130556e+04 232 f2ff9ae5 34480152 0.000000e+00 5.591168e+01 1.328211e+01 1.241239e+04 7.331618e+05 222 #################### # 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 4 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda4_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 4af260f6 14678040 0.000000e+00 2.604823e+01 3.286196e+00 1.130493e+04 2.991603e+05 434 fb4b8624 4427800 0.000000e+00 2.652276e+01 4.354433e+00 7.850738e+03 2.138358e+05 296 f2ff9ae5 34480152 0.000000e+00 2.714414e+01 3.836601e+00 1.555359e+04 4.306232e+05 573 #################### # 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 1 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda1_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 4af260f6 14678040 0.000000e+00 2.599288e+01 3.808778e+00 1.115095e+04 2.960687e+05 429 fb4b8624 4427800 0.000000e+00 2.539365e+01 2.861737e+00 6.678529e+03 1.717461e+05 263 f2ff9ae5 34480152 0.000000e+00 2.629746e+01 2.517281e+00 1.159718e+04 3.077710e+05 441 #################### # 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 4af260f6 14678040 0.000000e+00 2.561750e+01 2.633232e+00 1.155349e+04 2.990988e+05 451 fb4b8624 4427800 0.000000e+00 2.673210e+01 4.378492e+00 1.031859e+04 2.832378e+05 386 f2ff9ae5 34480152 0.000000e+00 2.631930e+01 2.903449e+00 1.339652e+04 3.568781e+05 509 #################### # 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 6 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda6_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 4af260f6 14678040 0.000000e+00 2.607685e+01 3.121182e+00 7.979517e+03 2.110617e+05 306 fb4b8624 4427800 0.000000e+00 2.621449e+01 3.800716e+00 7.654632e+03 2.048804e+05 292 f2ff9ae5 34480152 0.000000e+00 2.661811e+01 2.706929e+00 1.810031e+04 4.867788e+05 680 #################### # COMB_5 # 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 (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 # hash size flops mean (us) dev (us) sum sum2 n 4af260f6 14678040 0.000000e+00 2.759081e+01 5.463486e+00 5.435390e+03 1.558472e+05 197 fb4b8624 4427800 0.000000e+00 2.575898e+01 3.723342e+00 7.779212e+03 2.045713e+05 302 f2ff9ae5 34480152 0.000000e+00 2.684177e+01 3.098778e+00 1.181038e+04 3.212366e+05 440 #################### # COMB_6 # 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 (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 # hash size flops mean (us) dev (us) sum sum2 n 4af260f6 14678040 0.000000e+00 2.613306e+01 2.901462e+00 1.100202e+04 2.910606e+05 421 fb4b8624 4427800 0.000000e+00 2.615768e+01 3.461177e+00 7.010257e+03 1.865826e+05 268 f2ff9ae5 34480152 0.000000e+00 2.749333e+01 3.923485e+00 1.492888e+04 4.188033e+05 543 #################### # COMB_7 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4) 1 #################### # DEV_0 # device id 5 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda5_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 # hash size flops mean (us) dev (us) sum sum2 n 4af260f6 14678040 0.000000e+00 2.628755e+01 3.829892e+00 1.025215e+04 2.752243e+05 390 fb4b8624 4427800 0.000000e+00 2.540957e+01 3.333356e+00 8.258109e+03 2.134461e+05 325 f2ff9ae5 34480152 0.000000e+00 2.728087e+01 3.903560e+00 1.404965e+04 3.911340e+05 515 #################### # COMB_8 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4) 1 #################### # DEV_0 # device id 7 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda7_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 # hash size flops mean (us) dev (us) sum sum2 n 4af260f6 14678040 0.000000e+00 2.705248e+01 4.049710e+00 1.163257e+04 3.217418e+05 430 fb4b8624 4427800 0.000000e+00 2.626990e+01 3.774104e+00 6.908983e+03 1.852444e+05 263 f2ff9ae5 34480152 0.000000e+00 2.670502e+01 3.597311e+00 1.303205e+04 3.543362e+05 488