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Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Very Good. Zustand des Schutzumschlags: No Dust Jacket. 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. Ex-Library.

Zustand: New. In.

Paper covers. Zustand: Fine. No Jacket. Bryophytorum Bibliotheca t. 52. Scarcely used. Weight: 1.0 Language: German.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains papers presented at a workshop on the useof parallel techniques in symbolic and algebraic computationheld at Cornell University in May 1990. The eight papers inthe book fall into three groups.The first three papers discuss particular programmingsubstrates for parallel symbolic computation, especially fordistributed memory machines. The next three papers discussnovel ways of computing with elements of finite fields andwith algebraic numbers. The finite field technique isespecially interesting since it uses the Connection Machine,a SIMD machine, to achievesurprising amounts ofparallelism. One of the parallel computing substrates isalso used to implement a real root isolation technique.One of the crucial algorithms in modern algebraiccomputation is computing the standard, or Gr|bner, basis ofan ideal. The final two papers discuss two differentapproaches to speeding their computation. One uses vectorprocessing on the Cray and achieves significant speed-ups.The other uses a distributed memory multiprocessor andeffectively explores the trade-offs involved with differentinterconnect topologies of the multiprocessors.

Taschenbuch. Zustand: Neu. Computer Algebra and Parallelism | Second International Workshop, Ithaca, USA, May 9-11, 1990. Proceedings | Richard E. Zippel | Taschenbuch | xi | Englisch | 1992 | Springer | EAN 9783540553281 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 363 | Sprache: Englisch | Produktart: Bücher | Effective Polynomial Computation is an introduction to the algorithms of computer algebra. It discusses the basic algorithms for manipulating polynomials including factoring polynomials. These algorithms are discussed from both a theoretical and practical perspective. Those cases where theoretically optimal algorithms are inappropriate are discussed and the practical alternatives are explained. Effective Polynomial Computation provides much of the mathematical motivation of the algorithms discussed to help the reader appreciate the mathematical mechanisms underlying the algorithms, and so that the algorithms will not appear to be constructed out of whole cloth. Preparatory to the discussion of algorithms for polynomials, the first third of this book discusses related issues in elementary number theory. These results are either used in later algorithms (e.g. the discussion of lattices and Diophantine approximation), or analogs of the number theoretic algorithms are used for polynomial problems (e.g. Euclidean algorithm and p-adic numbers). Among the unique features of Effective Polynomial Computation is the detailed material on greatest common divisor and factoring algorithms for sparse multivariate polynomials. In addition, both deterministic and probabilistic algorithms for irreducibility testing of polynomials are discussed.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book contains papers presented at a workshop on the useof parallel techniques in symbolic and algebraic computationheld at Cornell University in May 1990. The eight papers inthe book fall into three groups.The first three papers discuss particular programmingsubstrates for parallel symbolic computation, especially fordistributed memory machines. The next three papers discussnovel ways of computing with elements of finite fields andwith algebraic numbers. The finite field technique isespecially interesting since it uses the Connection Machine,a SIMD machine, to achievesurprising amounts ofparallelism. One of the parallel computing substrates isalso used to implement a real root isolation technique.One of the crucial algorithms in modern algebraiccomputation is computing the standard, or Gr|bner, basis ofan ideal. The final two papers discuss two differentapproaches to speeding their computation. One uses vectorprocessing on the Cray and achieves significant speed-ups.The other uses a distributed memory multiprocessor andeffectively explores the trade-offs involved with differentinterconnect topologies of the multiprocessors.

Buch. Zustand: Neu. Neuware - Effective Polynomial Computation is an introduction to the algorithms of computer algebra. It discusses the basic algorithms for manipulating polynomials including factoring polynomials. These algorithms are discussed from both a theoretical and practical perspective. Those cases where theoretically optimal algorithms are inappropriate are discussed and the practical alternatives are explained. Effective Polynomial Computation provides much of the mathematical motivation of the algorithms discussed to help the reader appreciate the mathematical mechanisms underlying the algorithms, and so that the algorithms will not appear to be constructed out of whole cloth. Preparatory to the discussion of algorithms for polynomials, the first third of this book discusses related issues in elementary number theory. These results are either used in later algorithms (e.g. the discussion of lattices and Diophantine approximation), or analogs of the number theoretic algorithms are used for polynomial problems (e.g. Euclidean algorithm and p-adic numbers). Among the unique features of Effective Polynomial Computation is the detailed material on greatest common divisor and factoring algorithms for sparse multivariate polynomials. In addition, both deterministic and probabilistic algorithms for irreducibility testing of polynomials are discussed.