Name
Abstract | ||
|---|---|---|
New features of our DSC system for distributing a symbolic computation task over a network of processors are described. A new scheduler sends parallel subtasks to those compute nodes that are best suited in handling the added load of CPU usage and memory. Furthermore, a subtask can communicate back to the process that spawned it by a co-routine style calling mechanism. Two large experiments are described in this improved setting. In the first we have implemented an algorithm that can prove a number of more than 1,000 decimal digits prime in about 2 months elapsed time on some 20 computers. In the second a parallel version of a sparse linear system solver is used to compute the solution of sparse linear systems over finite fields. We are able to find the solution of a 100,000 by 100,000 linear system with about 10.3 million non-zero entries over the Galois field with 2 elements using 3 computers in about 54 hours CPU time. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1006/jsco.1995.1015 | J. Symb. Comput. |
Keywords | Field | DocType |
process scheduling,large sparse linear system,galois field,linear system,symbolic computation,finite field | Finite field,Linear system,Scheduling (computing),CPU time,Parallel computing,Sparse approximation,Symbolic computation,Theoretical computer science,Solver,Decimal,Mathematics | Journal |
Volume | Issue | ISSN |
19 | 1-3 | Journal of Symbolic Computation |
ISBN | Citations | PageRank |
3-540-57235-X | 9 | 0.96 |
References | Authors | |
11 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Angel Díaz | 1 | 9 | 0.96 |
| Martin Hitz | 2 | 95 | 14.38 |
| Erich Kaltofen | 3 | 2332 | 261.40 |
| Austin Lobo | 4 | 45 | 5.51 |
| T. Valente | 5 | 9 | 0.96 |