################## # 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 2.985465e+01 6.158621e+00 3.552703e+03 1.105782e+05 119 fb4b8624 4427800 0.000000e+00 1.132689e+01 2.249702e+00 2.423954e+03 2.853894e+04 214 f2ff9ae5 34480152 0.000000e+00 5.622304e+01 1.121739e+01 9.276802e+03 5.423319e+05 165 #################### # 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 2.632587e+01 4.244468e+00 1.174134e+04 3.171360e+05 446 fb4b8624 4427800 0.000000e+00 2.560067e+01 2.946464e+00 6.809779e+03 1.766442e+05 266 f2ff9ae5 34480152 0.000000e+00 2.687395e+01 3.041318e+00 1.378634e+04 3.752385e+05 513 #################### # 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 2.682825e+01 3.688517e+00 9.309402e+03 2.544759e+05 347 fb4b8624 4427800 0.000000e+00 2.601287e+01 3.034296e+00 6.711320e+03 1.769561e+05 258 f2ff9ae5 34480152 0.000000e+00 2.650277e+01 3.250317e+00 1.327789e+04 3.571937e+05 501 #################### # 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 2.844841e+01 4.987346e+00 1.118023e+04 3.278350e+05 393 fb4b8624 4427800 0.000000e+00 2.545228e+01 3.038424e+00 7.533874e+03 1.944869e+05 296 f2ff9ae5 34480152 0.000000e+00 2.671593e+01 2.977811e+00 9.510870e+03 2.572485e+05 356 #################### # 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 2.683154e+01 3.643920e+00 1.145707e+04 3.130806e+05 427 fb4b8624 4427800 0.000000e+00 2.439165e+01 2.519213e+00 6.951620e+03 1.713702e+05 285 f2ff9ae5 34480152 0.000000e+00 2.686670e+01 3.337051e+00 1.332588e+04 3.635460e+05 496 #################### # 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 2.743422e+01 5.313897e+00 8.504608e+03 2.420709e+05 310 fb4b8624 4427800 0.000000e+00 2.591823e+01 3.009457e+00 7.879143e+03 2.069667e+05 304 f2ff9ae5 34480152 0.000000e+00 2.671837e+01 2.963498e+00 1.282482e+04 3.468736e+05 480 #################### # 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 2.572873e+01 2.716127e+00 1.232406e+04 3.206163e+05 479 fb4b8624 4427800 0.000000e+00 2.555023e+01 2.989409e+00 6.362008e+03 1.647760e+05 249 f2ff9ae5 34480152 0.000000e+00 2.648407e+01 2.593556e+00 1.504295e+04 4.022192e+05 568 #################### # 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 2.535931e+01 2.801001e+00 7.303480e+03 1.874707e+05 288 fb4b8624 4427800 0.000000e+00 2.706983e+01 4.764143e+00 1.228970e+04 3.429847e+05 454 f2ff9ae5 34480152 0.000000e+00 2.645378e+01 3.704623e+00 1.251264e+04 3.374982e+05 473 #################### # 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 2.565071e+01 2.881053e+00 1.064505e+04 2.764977e+05 415 fb4b8624 4427800 0.000000e+00 2.622930e+01 4.388391e+00 8.262230e+03 2.227788e+05 315 f2ff9ae5 34480152 0.000000e+00 2.628917e+01 2.974884e+00 1.204044e+04 3.205863e+05 458