| commit | b22d063075ec545a59a25abd5d83e4642dc329c2 | [log] [tgz] |
|---|---|---|
| author | Sameer Agarwal <sameeragarwal@google.com> | Thu Aug 15 22:55:23 2013 -0700 |
| committer | Sameer Agarwal <sameeragarwal@google.com> | Fri Aug 16 10:48:54 2013 -0700 |
| tree | 0529893c06e6ef5837468563314d80340053c8cc | |
| parent | f258e4624f5bd86105ea28b9b92dd70a3f4a3a44 [diff] |
Reduce memory usage in covariance estimation. When using the SPARSE_QR algorithm, now a Q-less factorization is used. This results in significantly less memory usage. The inversion of the semi-normal equations is now threaded using openmp. Indeed if one has SuiteSparse compiled with TBB, then both the factorization and the inversion are completely threaded. Change-Id: Ia07591e48e7958d427ef91ff9e67662f6e982c21