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- ##################
- # Performance Model Version
- 44
- ####################
- # COMBs
- # number of combinations
- 9
- ####################
- # COMB_0
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 0
- ####################
- # DEV_0
- # device id
- 0
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cpu0_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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.985465e+01 6.158621e+00 3.552703e+03 1.105782e+05 119
- fb4b8624 4427800 0.000000e+00 1.132689e+01 2.249702e+00 2.423954e+03 2.853894e+04 214
- f2ff9ae5 34480152 0.000000e+00 5.622304e+01 1.121739e+01 9.276802e+03 5.423319e+05 165
- ####################
- # COMB_2
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 1
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda1_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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.632587e+01 4.244468e+00 1.174134e+04 3.171360e+05 446
- fb4b8624 4427800 0.000000e+00 2.560067e+01 2.946464e+00 6.809779e+03 1.766442e+05 266
- f2ff9ae5 34480152 0.000000e+00 2.687395e+01 3.041318e+00 1.378634e+04 3.752385e+05 513
- ####################
- # COMB_6
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 3
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda3_impl0 (Comb6)
- # 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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.682825e+01 3.688517e+00 9.309402e+03 2.544759e+05 347
- fb4b8624 4427800 0.000000e+00 2.601287e+01 3.034296e+00 6.711320e+03 1.769561e+05 258
- f2ff9ae5 34480152 0.000000e+00 2.650277e+01 3.250317e+00 1.327789e+04 3.571937e+05 501
- ####################
- # COMB_5
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 0
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda0_impl0 (Comb5)
- # 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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.844841e+01 4.987346e+00 1.118023e+04 3.278350e+05 393
- fb4b8624 4427800 0.000000e+00 2.545228e+01 3.038424e+00 7.533874e+03 1.944869e+05 296
- f2ff9ae5 34480152 0.000000e+00 2.671593e+01 2.977811e+00 9.510870e+03 2.572485e+05 356
- ####################
- # COMB_7
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 5
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda5_impl0 (Comb7)
- # 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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.683154e+01 3.643920e+00 1.145707e+04 3.130806e+05 427
- fb4b8624 4427800 0.000000e+00 2.439165e+01 2.519213e+00 6.951620e+03 1.713702e+05 285
- f2ff9ae5 34480152 0.000000e+00 2.686670e+01 3.337051e+00 1.332588e+04 3.635460e+05 496
- ####################
- # COMB_8
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 7
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda7_impl0 (Comb8)
- # 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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.743422e+01 5.313897e+00 8.504608e+03 2.420709e+05 310
- fb4b8624 4427800 0.000000e+00 2.591823e+01 3.009457e+00 7.879143e+03 2.069667e+05 304
- f2ff9ae5 34480152 0.000000e+00 2.671837e+01 2.963498e+00 1.282482e+04 3.468736e+05 480
- ####################
- # COMB_1
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 4
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda4_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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.572873e+01 2.716127e+00 1.232406e+04 3.206163e+05 479
- fb4b8624 4427800 0.000000e+00 2.555023e+01 2.989409e+00 6.362008e+03 1.647760e+05 249
- f2ff9ae5 34480152 0.000000e+00 2.648407e+01 2.593556e+00 1.504295e+04 4.022192e+05 568
- ####################
- # COMB_4
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 6
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda6_impl0 (Comb4)
- # 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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.535931e+01 2.801001e+00 7.303480e+03 1.874707e+05 288
- fb4b8624 4427800 0.000000e+00 2.706983e+01 4.764143e+00 1.228970e+04 3.429847e+05 454
- f2ff9ae5 34480152 0.000000e+00 2.645378e+01 3.704623e+00 1.251264e+04 3.374982e+05 473
- ####################
- # COMB_3
- # number of types devices
- 1
- ####################
- # DEV_0
- # device type (CPU - 0, CUDA - 1, OPENCL - 2, MIC - 3, SCC - 4)
- 1
- ####################
- # DEV_0
- # device id
- 2
- ####################
- # DEV_0
- # number of cores
- 1
- ##########
- # number of implementations
- 1
- #####
- # Model for cuda2_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
- # hash size flops mean (us) dev (us) sum sum2 n
- 4af260f6 14678040 0.000000e+00 2.565071e+01 2.881053e+00 1.064505e+04 2.764977e+05 415
- fb4b8624 4427800 0.000000e+00 2.622930e+01 4.388391e+00 8.262230e+03 2.227788e+05 315
- f2ff9ae5 34480152 0.000000e+00 2.628917e+01 2.974884e+00 1.204044e+04 3.205863e+05 458
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