################## # Performance Model Version 45 #################### # COMBs # number of combinations 9 #################### # 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 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 0b0b0ce8 3686400 2.621440e+08 6.801013e+02 7.013561e+01 4.760709e+04 3.272198e+07 70 4220e23d 14745600 2.097152e+09 5.623635e+03 5.419920e+02 4.442672e+05 2.521603e+09 79 492beed5 33177600 7.077888e+09 1.150361e+04 5.884814e+02 1.000814e+06 1.154310e+10 87 24c84a50 11059200 1.769472e+09 2.875903e+03 1.471204e+02 2.502035e+05 7.214438e+08 87 #################### # COMB_4 # 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 (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 0b0b0ce8 3686400 2.621440e+08 6.717051e+02 6.137607e+01 4.500424e+04 3.048197e+07 67 4220e23d 14745600 2.097152e+09 5.648275e+03 4.677390e+02 4.575103e+05 2.601865e+09 81 492beed5 33177600 7.077888e+09 1.157020e+04 6.521027e+02 1.018178e+06 1.181795e+10 88 24c84a50 11059200 1.769472e+09 2.892550e+03 1.630257e+02 2.545445e+05 7.386219e+08 88 #################### # COMB_6 # 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 (Comb6) # 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 0b0b0ce8 3686400 2.621440e+08 6.265559e+02 5.536840e+01 4.824481e+04 3.046412e+07 77 4220e23d 14745600 2.097152e+09 5.631203e+03 4.767455e+02 4.561275e+05 2.586957e+09 81 492beed5 33177600 7.077888e+09 1.162826e+04 6.757302e+02 1.023286e+06 1.193922e+10 88 24c84a50 11059200 1.769472e+09 2.907065e+03 1.689325e+02 2.558215e+05 7.462012e+08 88 #################### # COMB_7 # 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 (Comb7) # 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 0b0b0ce8 3686400 2.621440e+08 6.780899e+02 4.241206e+01 4.543202e+04 3.092751e+07 67 4220e23d 14745600 2.097152e+09 5.857201e+03 8.346836e+02 4.744333e+05 2.835284e+09 81 492beed5 33177600 7.077888e+09 1.150498e+04 4.254093e+02 9.894285e+05 1.139892e+10 86 24c84a50 11059200 1.769472e+09 2.876245e+03 1.063523e+02 2.473571e+05 7.124325e+08 86 #################### # COMB_0 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 4 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda4_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 0b0b0ce8 3686400 2.621440e+08 6.759139e+02 4.092799e+01 4.190666e+04 2.842915e+07 62 4220e23d 14745600 2.097152e+09 5.527477e+03 2.733928e+02 4.421982e+05 2.450220e+09 80 492beed5 33177600 7.077888e+09 1.146770e+04 1.768909e+02 1.100899e+06 1.262778e+10 96 24c84a50 11059200 1.769472e+09 2.866925e+03 4.422272e+01 2.752248e+05 7.892362e+08 96 #################### # COMB_1 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 5 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda5_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 0b0b0ce8 3686400 2.621440e+08 6.339465e+02 7.125158e+01 4.184047e+04 2.685969e+07 66 4220e23d 14745600 2.097152e+09 5.624130e+03 4.755864e+02 4.668028e+05 2.644133e+09 83 492beed5 33177600 7.077888e+09 1.149102e+04 5.375188e+02 1.114629e+06 1.283625e+10 97 24c84a50 11059200 1.769472e+09 2.872755e+03 1.343797e+02 2.786572e+05 8.022656e+08 97 #################### # COMB_3 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 6 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda6_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 0b0b0ce8 3686400 2.621440e+08 6.389750e+02 8.615382e+01 4.728415e+04 3.076266e+07 74 4220e23d 14745600 2.097152e+09 5.648331e+03 5.220897e+02 4.631632e+05 2.638450e+09 82 492beed5 33177600 7.077888e+09 1.155069e+04 5.660846e+02 1.108866e+06 1.283893e+10 96 24c84a50 11059200 1.769472e+09 2.887673e+03 1.415212e+02 2.772165e+05 8.024331e+08 96 #################### # COMB_5 # number of types devices 1 #################### # DEV_0 # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3) 1 #################### # DEV_0 # device id 7 #################### # DEV_0 # number of cores 1 ########## # number of implementations 1 ##### # Model for cuda7_impl0 (Comb5) # 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 0b0b0ce8 3686400 2.621440e+08 6.386625e+02 8.094896e+01 4.342905e+04 2.818209e+07 68 4220e23d 14745600 2.097152e+09 5.638657e+03 3.709019e+02 4.454539e+05 2.522630e+09 79 492beed5 33177600 7.077888e+09 1.144012e+04 2.531108e+02 1.109691e+06 1.270122e+10 97 24c84a50 11059200 1.769472e+09 2.860030e+03 6.327770e+01 2.774228e+05 7.938262e+08 97 #################### # COMB_8 # 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 (Comb8) # 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 0b0b0ce8 3686400 2.621440e+08 1.414338e+04 6.441210e+02 3.535844e+05 5.011251e+09 25 4220e23d 14745600 2.097152e+09 1.091117e+05 2.701159e+03 3.382462e+06 3.692924e+11 31 492beed5 33177600 7.077888e+09 3.621356e+05 7.764608e+03 8.329119e+06 3.017657e+12 23 24c84a50 11059200 1.769472e+09 9.053390e+04 1.941152e+03 2.082280e+06 1.886036e+11 23