Computer Algebra and Parallelism: Second International Workshop Ithaca, USA, May 9-11, 1990 Proceedings (Lecture Notes in Computer Science 584)

Zippel, R. E. (ed.)

ISBN 10: 0387553282 / ISBN 13: 9780387553283

Published by Springer-Verlag, Berlin, 1992

About this Item

Lecture Notes in Computer Science 584; Ex-Library. Previous owner's sticker on the front cover. Ink stamp on half-title page. Library catalogue sticker inside front cover. Faintly bumped spine head and rubbed corners. Foot of page block slightly grubby and marked due to age. Sound, clean book with tight binding. ADG.

Seller Inventory # 094451

Bibliographic Details

• Title: Computer Algebra and Parallelism: Second International Workshop Ithaca, USA, May 9-11, 1990 Proceedings (Lecture Notes in Computer Science 584)
• Publisher: Springer-Verlag, Berlin
• Publication Date: 1992
• Language: English
• ISBN 10: 0387553282
• ISBN 13: 9780387553283
• Binding: Paperback
• Condition: Very Good
• Dust Jacket Condition: No Dust Jacket
• Book Type: Ex-Library
• Seller catalogs:
  • Computers & Technology (incl. AI)

About this title

Synopsis

This book contains papers presented at a workshop on the use of parallel techniques in symbolic and algebraic computation held at Cornell University in May 1990. The eight papers in the book fall into three groups. The first three papers discuss particular programming substrates for parallel symbolic computation, especially for distributed memory machines. The next three papers discuss novel ways of computing with elements of finite fields and with algebraic numbers. The finite field technique is especially interesting since it uses the Connection Machine, a SIMD machine, to achieve surprising amounts of parallelism. One of the parallel computing substrates is also used to implement a real root isolation technique. One of the crucial algorithms in modern algebraic computation is computing the standard, or Gröbner, basis of an ideal. The final two papers discuss two different approaches to speeding their computation. One uses vector processing on the Cray and achieves significant speed-ups. The other uses a distributed memory multiprocessor and effectively explores the trade-offs involved with different interconnect topologies of the multiprocessors.