################## # Performance Model Version 45 #################### # COMBs # number of combinations 5 #################### # COMB_4 # 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 (Comb4) # number of entries 4 # 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 8cfc3ba0 24883200 0.000000e+00 1.164877e+05 2.576301e+04 2.054842e+08 2.510721e+13 1764 f0ac7beb 4915200 0.000000e+00 1.087142e+04 2.109400e+03 2.505863e+07 2.826792e+11 2305 d46431bb 1228800 0.000000e+00 1.613402e+03 3.115535e+02 8.438094e+06 1.412169e+10 5230 24c84a50 11059200 0.000000e+00 3.517390e+04 7.045528e+03 6.925741e+07 2.533794e+12 1969 #################### # COMB_1 # 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 (Comb1) # number of entries 4 # 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 8cfc3ba0 24883200 0.000000e+00 2.688252e+03 2.597845e+02 1.459721e+07 3.960743e+10 5430 f0ac7beb 4915200 0.000000e+00 2.657700e+02 2.996380e+01 1.356225e+06 3.650255e+08 5103 d46431bb 1228800 0.000000e+00 6.142508e+01 1.012391e+01 4.393736e+05 2.772170e+07 7153 24c84a50 11059200 0.000000e+00 7.851775e+02 4.684799e+01 4.315336e+06 3.400367e+09 5496 #################### # COMB_0 # 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 (Comb0) # number of entries 4 # 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 8cfc3ba0 24883200 0.000000e+00 2.707789e+03 2.773178e+02 1.421860e+07 3.890480e+10 5251 f0ac7beb 4915200 0.000000e+00 2.693001e+02 2.710216e+01 1.308798e+06 3.560293e+08 4860 d46431bb 1228800 0.000000e+00 6.592485e+01 1.426453e+01 1.071279e+05 7.393038e+06 1625 24c84a50 11059200 0.000000e+00 7.926860e+02 4.760061e+01 4.363736e+06 3.471546e+09 5505 #################### # COMB_2 # 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 (Comb2) # number of entries 4 # 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 8cfc3ba0 24883200 0.000000e+00 2.706383e+03 2.631153e+02 1.444938e+07 3.947516e+10 5339 f0ac7beb 4915200 0.000000e+00 2.686331e+02 2.912062e+01 1.401996e+06 3.810483e+08 5219 d46431bb 1228800 0.000000e+00 6.317490e+01 1.087216e+01 2.866877e+05 1.864788e+07 4538 24c84a50 11059200 0.000000e+00 7.922324e+02 5.091772e+01 4.156844e+06 3.306790e+09 5247 #################### # COMB_3 # 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 (Comb3) # number of entries 4 # 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 8cfc3ba0 24883200 0.000000e+00 2.681149e+03 2.665822e+02 1.451306e+07 3.929636e+10 5413 f0ac7beb 4915200 0.000000e+00 2.642224e+02 2.666799e+01 1.450317e+06 3.871098e+08 5489 d46431bb 1228800 0.000000e+00 5.975719e+01 9.345113e+00 4.033610e+05 2.469321e+07 6750 24c84a50 11059200 0.000000e+00 7.867204e+02 4.699968e+01 4.148377e+06 3.275261e+09 5273