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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 9830400 0.000000e+00 5.319005e+04 1.072845e+03 1.074439e+08 5.717271e+12 2020
- 24c84a50 22118400 0.000000e+00 1.747556e+05 3.288616e+03 2.457064e+08 4.295378e+13 1406
- d46431bb 2457600 0.000000e+00 6.731248e+03 2.017842e+02 1.758875e+07 1.185006e+11 2613
- ####################
- # 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 9830400 0.000000e+00 1.857771e+03 5.953793e+01 1.442559e+07 2.682697e+10 7765
- 24c84a50 22118400 0.000000e+00 5.825821e+03 1.536397e+02 3.023019e+07 1.762382e+11 5189
- d46431bb 2457600 0.000000e+00 2.626388e+02 2.130047e+01 1.891262e+06 4.999858e+08 7201
- ####################
- # 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
- f0ac7beb 9830400 0.000000e+00 1.841710e+03 6.898710e+01 1.448873e+07 2.672149e+10 7867
- 24c84a50 22118400 0.000000e+00 5.866678e+03 1.842980e+02 2.977339e+07 1.748433e+11 5075
- d46431bb 2457600 0.000000e+00 2.614108e+02 2.029949e+01 1.936531e+06 5.092829e+08 7408
- ####################
- # COMB_1
- # 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 (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 9830400 0.000000e+00 1.853277e+03 6.983878e+01 1.439996e+07 2.672502e+10 7770
- 24c84a50 22118400 0.000000e+00 5.858635e+03 1.761006e+02 3.008995e+07 1.764453e+11 5136
- d46431bb 2457600 0.000000e+00 2.701366e+02 1.779276e+01 1.899060e+06 5.152311e+08 7030
|
