Semidefinite Programming Relaxation vs Polyhedral Homotopy ...

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Numerical results: Hardware — PC cluster (AMD Athlon 2.0GHz)Problem cpu time speedup(#sol) #CPUs in second rationoon-10 1 62,672 1.0(59,029) 40 1,797 34.9eco-14 1 22,653 1.0(4,096) 40 626 36.2Workshop on Advances in Optimization, April 19-21, 2007 – p.5/24
Numerical results: Hardware — PC cluster (AMD Athlon 2.0GHz)Problem cpu time speedup(#sol) #CPUs in second rationoon-10 1 62,672 1.0(59,029) 40 1,797 34.9eco-14 1 22,653 1.0(4,096) 40 626 36.2Problem #CPUs in second speedupnoon-12 40 49,458(531,417)eco-16 40 12,051(16,384)Workshop on Advances in Optimization, April 19-21, 2007 – p.5/24
Page 1 and 2: Semidefinite Programming Relaxation
Page 3 and 4: Contents1. PHoMpara — Parallel im
Page 5: The polyhedral homotopy methodImple
Page 9 and 10: POP min. f 0 (x) s.t. f j (x) ≥ 0
Page 11 and 12: POP min. f 0 (x) s.t. f j (x) ≥ 0
Page 13 and 14: Sparse (SDP) relaxation = Lasserre
Page 17 and 18: A POP alkyl from globalibmin − 6.
Page 19 and 20: Systems of polynomial equationsIs t
Page 21 and 22: Katsura n system of polynomial equa
Page 23 and 24: Katsura n system of polynomial equa
Page 25 and 26: cyclic n system of polynomial equat
Page 27 and 28: Discretization of Mimura’s ODE wi
Page 33 and 34: Discretization of DAE with 3 unknow
Page 35 and 36: 21.81.61.41.210.80.60.40.200 0.2 0.
Page 39 and 40: Some essential differences between
Page 41 and 42: Some essential differences between

Semidefinite Programming Relaxation vs Polyhedral Homotopy ...

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