A Fast Solver for HSS Representations via Sparse Matrices

نویسندگان

  • Shivkumar Chandrasekaran
  • Patrick Dewilde
  • Ming Gu
  • W. Lyons
  • T. Pals
چکیده

In this paper we present a fast direct solver for certain classes of dense structured linear systems that works by first converting the given dense system to a larger system of block sparse equations and then uses standard sparse direct solvers. The kind of matrix structures that we consider are induced by numerical low rank in the off-diagonal blocks of the matrix and are related to the structures exploited by the fast multipole method (FMM) of Greengard and Rokhlin. The special structure that we exploit in this paper is captured by what we term the hierarchically semiseparable (HSS) representation of a matrix. Numerical experiments indicate that the method is probably backward stable.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Superfast Multifrontal Method for Large Structured Linear Systems of Equations

In this paper we develop a fast direct solver for large discretized linear systems using the supernodal multifrontal method together with low-rank approximations. For linear systems arising from certain partial differential equations such as elliptic equations, during the Gaussian elimination of the matrices with proper ordering, the fill-in has a low-rank property: all off-diagonal blocks have...

متن کامل

Mfrs: an Algorithm for the Structured Multifrontal Solution of Large Sparse Matrices via Randomized Sampling

This paper presents strategies for the development of an efficient algorithm (MFRS) for the direct solutions of large sparse linear systems. The algorithm is based on a structured multifrontal method with randomized sampling. We propose data structures and access schemes for a type of rank structured matrices, called Hierarchically SemiSeparable (HSS) forms. A data tree structure is used for HS...

متن کامل

An efficient multi-core implementation of a novel HSS-structured multifrontal solver using randomized sampling

We present a sparse linear system solver that is based on a multifrontal variant of Gaussian elimination, and exploits low-rank approximation of the resulting dense frontal matrices. We use hierarchically semiseparable (HSS) matrices, which have low-rank off-diagonal blocks, to approximate the frontal matrices. For HSS matrix construction, a randomized sampling algorithm is used together with i...

متن کامل

Efficient Parallel Algorithms for Hierarchically Semiseparable Matrices

Recently, hierarchically semiseparable (HSS) matrices have been used in the development of fast direct sparse solvers. Key applications of HSS algorithms, coupled with multifrontal solvers, appear in solving certain large-scale computational inverse problems. Here, we develop massively parallel HSS algorithms appearing in these solution methods, namely, parallel HSS construction using the rank ...

متن کامل

Superfast Multifrontal Method for Structured Linear Systems of Equations

In this paper we develop a fast direct solver for discretized linear systems using the multifrontal method together with low-rank approximations. For linear systems arising from certain partial differential equations such as elliptic equations we discover that during the Gaussian elimination of the matrices with proper ordering, the fill-in has a low-rank property: all off-diagonal blocks have ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • SIAM J. Matrix Analysis Applications

دوره 29  شماره 

صفحات  -

تاریخ انتشار 2006