A Parallel Approximation Algorithm for Positive Semidefinite Programming

Details A Parallel Approximation Algorithm for Positive Semidefinite Programming A Parallel Approximation Algorithm for Positive Semidefinite Programming

2011-04-13

arxiv.org/abs/1104.2502v1

Computer Science

Computational Complexity

16 pages

Scientific paper

Positive semidefinite programs are an important subclass of semidefinite programs in which all matrices involved in the specification of the problem are positive semidefinite and all scalars involved are non-negative. We present a parallel algorithm, which given an instance of a positive semidefinite program of size N and an approximation factor eps > 0, runs in (parallel) time poly(1/eps) \cdot polylog(N), using poly(N) processors, and outputs a value which is within multiplicative factor of (1 + eps) to the optimal. Our result generalizes analogous result of Luby and Nisan [1993] for positive linear programs and our algorithm is inspired by their algorithm.

Affiliated with

Also associated with

No associations

Rating

A Parallel Approximation Algorithm for Positive Semidefinite Programming does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Parallel Approximation Algorithm for Positive Semidefinite Programming, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Parallel Approximation Algorithm for Positive Semidefinite Programming will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-218899