################## # Performance Model Version 45 #################### # COMBs # number of combinations 4 #################### # COMB_3 # 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 (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 afdd228b 1638400 0.000000e+00 4.182946e+04 4.195402e+03 1.171225e+06 4.948453e+10 28 617e5fe6 3686400 0.000000e+00 1.431791e+05 1.961610e+04 1.431791e+06 2.088506e+11 10 cea37d6d 409600 0.000000e+00 4.839229e+03 3.061560e+02 1.258200e+05 6.113086e+08 26 #################### # COMB_2 # 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 (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 afdd228b 1638400 0.000000e+00 2.565619e+04 2.729977e+03 4.618114e+05 1.198247e+10 18 617e5fe6 3686400 0.000000e+00 5.517976e+04 5.023576e+03 8.828762e+05 4.912068e+10 16 cea37d6d 409600 0.000000e+00 9.325377e+03 4.741281e+02 9.325377e+04 8.718745e+08 10 #################### # COMB_1 # 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 (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 afdd228b 1638400 0.000000e+00 2.512124e+04 2.223761e+03 4.773036e+05 1.208442e+10 19 617e5fe6 3686400 0.000000e+00 5.116041e+04 1.272422e+03 7.674062e+05 3.928511e+10 15 cea37d6d 409600 0.000000e+00 9.353760e+03 7.152342e+02 9.353760e+04 8.800438e+08 10 #################### # 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 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 afdd228b 1638400 0.000000e+00 2.814234e+04 3.880171e+03 5.065622e+05 1.452685e+10 18 617e5fe6 3686400 0.000000e+00 5.467956e+04 6.741916e+03 8.201934e+05 4.552961e+10 15 cea37d6d 409600 0.000000e+00 1.004502e+04 9.839619e+02 1.004502e+05 1.018706e+09 10