Luke Erlandson
Hierarchical matrices are scalable matrix representations particularly when the matrix entries are defined by a kernel function evaluated between pairs of points. In this paper, we present a new scheme to alleviate the computational bottlenecks present in many hierarchical matrix methods. For general kernel functions, a popular approach to construct hierarchical matrices is through interpolation, due to its efficiency compared to computationally expensive algebraic techniques. However, interpolation-based m
This paper presents an efficient method to perform structured matrix approximation by separation and hierarchy (SMASH), when the original dense matrix is associated with a kernel function. Given the points in a domain, a tree structure is first constructed based on an adaptive partition of the computational domain to facilitate subsequent approximation procedures. In contrast to existing schemes based on either analytic or purely algebraic approximations, SMASH takes advantage of both approaches and greatly
For more information, contact Lucas "Luke" Erlandson ( [email protected] )
Luke Erlandson