Abstract
It is widely acknowledged in high-performance computing circles that parallel input/output needs substantial improvement in order to make scalable computers truly usable. We present a data storage model that allows processors independent access to their own data and a corresponding compilation strategy that integrates data-parallel computation with data distribution for out-of-core problems. Our results compare several communication methods and I/O optimizations using two out-of-core problems, Jacobi iteration and LU factorization.
Original language | English (US) |
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Pages (from-to) | 1-10 |
Number of pages | 10 |
Journal | ACM SIGPLAN Notices |
Volume | 30 |
Issue number | 8 |
DOIs | |
State | Published - Jan 1995 |
ASJC Scopus subject areas
- Software
- Computer Graphics and Computer-Aided Design