Numerical Evaluation of SDPA (SemiDefinite Programming Algorithm)
Katsuki Fujisawa, Mituhiro Fukuda, Masakazu Kojima and Kazuhide Nakata
SDPA (SemiDefinite Programming Algorithm) is a C++ implementation of a
Mehrotra-type primal-dual predictor-corrector interior-point method
for solving the standard form semidefinite program and its dual. We
report numerical results of large scale problems to evaluate its
performance, and investigate how major time-consuming parts of SDPA
vary with the problem size, the number of constraints and the sparsity
of data matrices.
Research Report B-330,
Department of Mathematical and Computing Sciences,
Tokyo Institute of Technology,
Oh-Okayama, Meguro-ku, Tokyo 152, September 1997.