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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
- f0ac7beb 4915200 0.000000e+00 2.587052e+04 1.487038e+03 5.386241e+07 1.398052e+12 2082
- 24c84a50 11059200 0.000000e+00 8.218890e+04 3.347888e+03 1.244340e+08 1.024406e+13 1514
- d46431bb 1228800 0.000000e+00 3.265838e+03 1.561177e+02 8.347482e+06 2.732382e+10 2556
- ####################
- # 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
- f0ac7beb 4915200 0.000000e+00 9.047163e+02 4.943457e+01 7.022408e+06 6.372255e+09 7762
- 24c84a50 11059200 0.000000e+00 2.963966e+03 7.453353e+01 1.530888e+07 4.540369e+10 5165
- d46431bb 1228800 0.000000e+00 1.924610e+02 1.043827e+01 8.556817e+05 1.651698e+08 4446
- ####################
- # 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
- f0ac7beb 4915200 0.000000e+00 8.810829e+02 4.167975e+01 6.874209e+06 6.070301e+09 7802
- 24c84a50 11059200 0.000000e+00 2.960803e+03 8.260112e+01 1.519780e+07 4.503271e+10 5133
- d46431bb 1228800 0.000000e+00 1.894698e+02 9.561378e+00 8.340462e+05 1.584290e+08 4402
- ####################
- # 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
- f0ac7beb 4915200 0.000000e+00 8.953024e+02 5.096374e+01 6.835634e+06 6.139790e+09 7635
- 24c84a50 11059200 0.000000e+00 2.963787e+03 5.048433e+01 1.524275e+07 4.518938e+10 5143
- d46431bb 1228800 0.000000e+00 1.803248e+02 8.617192e+00 8.859357e+05 1.601210e+08 4913
|
