Wavelet sparse approximate inverse preconditioners

We show how to use wavelet compression ideas to improve the performance of approximate inverse preconditioners. Our main idea is to first transform the inverse of the coefficient matrix into a wavelet basis, before applying standard approximate inverse techniques. In this process, smoothness in the entries ofA ⁻¹ are converted into small wavelet coefficients, thus allowing a more efficient approximate inverse approximation. We shall justify theoretically and numerically that our approach is effective for matrices with smooth inverses. Supported by grants from ONR: ONR-N00014-92-J-1890, and the Army Research Office: DAAL-03-91-C-0047 (Univ. of Tenn. subcontract ORA4466.04 Amendment 1 and 2). The first and the third author also acknowledge support from RIACS/NASA Ames NAS 2-96027 and the Alfred P. Sloan Foundation as Doctoral Dissertation Fellows, respectively. the work was supported by the Natural Sciences and Engineering Research Council of Canada, the Information Technology Research Centre (which is funded by the Province of Ontario), and RIACS/NASA Ames NAS 2-96027.