English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

SOLAR is a portable high-performance library for out-of-core dense matrix computations. It combines portability with high performance by using existing high-performance in-core subroutine lib raries and by using an optimized matrix input-output library. SOLAR works on parallel computers, workstations, and personal computers . It supports in-core computations on both shared-memory and distributed-memory machines, and its matrix input-output library supports bot h conven- tional I/O interfaces and parallel I/O interfaces. This pap er discusses the overall design of SOLAR, its interfaces, and the design of several important subroutines. Experimental results show that SOLAR can factor on a single workstation an out-of-core positive-definite symmet- ric matrix at a rate exceeding 215 Mflops, and an out-of-core g eneral matrix at a rate exceeding 195 Mflops. Less than 16% of the runn ing time is spent on I/O in these computations. These results indicate that SOLAR's portability does not compromise its performan ce. We expect that the combination of portability, modularity, an d the use of a high-level I/O interface will make the library an importan t platform for research on out-of-core algorithms and on parallel I/O. This paper describes the design and implementation of SOLAR, a high-performance portable library for out-of-core dense m atrix com- putations. SOLAR is designed to meet three main objectives. First, the library should deliver as much of the functionality of LAPACK (2), a public domain library for in-core matrix computations, as possible. Second, the library should be portable across a wide variety of ar- chitectures. Third, the library should deliver high perfor mance. The paper explains how the design allows us to achieve our objectives, and demonstrates that the implementation is indeed portable and achieves high performance. Our current implementation does not yet include the full functionality of LAPACK for out-of-core matrices, but it does include both sequential and parallel solvers for general an d positive- definite symmetric linear systems as well as several support routines. Although current computers, especially parallel computer s, have large amounts of memory, there is still a need for software fo r out- of-core matrix computations. Since DRAM is about 100 times more expensive than disk (18) and since out-of-core software for dense ma- trix computations can run at almost the rate of in-core softw are (see Section 4), out-of-core software can solve problems at a much lower cost-performance ratio than in-core software. Out-of-cor e solvers can be used for the overnight solution of very large problems on work- stations, for the solution of large problems in easy-to-use modeling environments such as Matlab, as well as for solving huge prob-

The design and implementation of SOLAR, a portable library for scalable out-of-core linear algebra computations