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- ##################
- # 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
- ff82dda0 14745600 0.000000e+00 8.795690e+04 4.598673e+03 1.715160e+07 1.512725e+12 195
- d39bff17 6553600 0.000000e+00 2.744119e+04 1.740624e+03 4.390591e+06 1.209678e+11 160
- 2c1922b7 1638400 0.000000e+00 4.091631e+03 5.062810e+02 7.283104e+05 3.025603e+09 178
- ####################
- # 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
- 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
- ff82dda0 14745600 0.000000e+00 6.847320e+03 1.168001e+03 8.285257e+05 5.838253e+09 121
- d39bff17 6553600 0.000000e+00 2.123746e+03 3.153004e+02 4.226254e+05 9.173322e+08 199
- 2c1922b7 1638400 0.000000e+00 5.446913e+02 9.530021e+01 1.040360e+05 5.840221e+07 191
- ####################
- # COMB_0
- # 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 (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
- ff82dda0 14745600 0.000000e+00 6.816836e+03 1.179433e+03 1.172496e+06 8.231973e+09 172
- d39bff17 6553600 0.000000e+00 2.055421e+03 3.154533e+02 3.864192e+05 8.129623e+08 188
- 2c1922b7 1638400 0.000000e+00 6.121868e+02 1.314710e+02 9.550115e+04 6.116094e+07 156
- ####################
- # COMB_2
- # 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 (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
- ff82dda0 14745600 0.000000e+00 6.940618e+03 1.147691e+03 1.006390e+06 7.175959e+09 145
- d39bff17 6553600 0.000000e+00 2.093041e+03 3.377347e+02 3.851195e+05 8.270585e+08 184
- 2c1922b7 1638400 0.000000e+00 6.098259e+02 1.286153e+02 1.091588e+05 6.952888e+07 179
|
