Abstract
In resent years, semidefinite program(SDP)has been intensively studied both in theoretical and practical aspects of various fields including interior-point methods, combinatorial optimization and the control and systems theory. The SDPA(SemiDefinite Programming Algorithm)[1]is an optimization software, implemented by C++ language, of a Mehrotra-type primal-dual predictor-corrector interior-point method for solving the standard form semidefinite program. In this paper, we also discuss parallel execution of the SDPA on the Ninf[3], a global network-wide computing infrastructure which has been developed for high-performance numerical computation services. We report some numerical results on a parallel implementation of the successive convex relaxation method proposed by Kojima and Tuncel[4]applying the SDPA on the Ninf.
| Translated title of the contribution | The SDPA (SemiDefinite Programming Algorithm) on the Ninf (A Network based Information Library for the Global Computing) |
|---|---|
| Original language | Japanese |
| Pages (from-to) | 31-36 |
| Number of pages | 6 |
| Journal | 情報処理学会研究報告グラフィクスとCAD（CG） |
| Volume | 86 |
| Publication status | Published - May 25 2001 |
| Externally published | Yes |