Opportunities and Constraints of Parallel Computing
Published on 25. October 1990
Book
Paperback/Softback
XI, 166 pages
978-1-4613-9670-3 (ISBN)
Description
At the initiative of the IBM Almaden Research Center and the National Science Foundation, a workshop on "Opportunities and Constraints of Parallel Computing" was held in San Jose, California, on December 5-6, 1988. The Steering Committee of the workshop consisted of Prof. R. Karp (University of California at Berkeley), Prof. L. Snyder (University of Washington at Seattle), and Dr. J. L. C. Sanz (IBM Almaden Research Center). This workshop was intended to provide a vehicle for interaction for people in the technical community actively engaged in research on parallel computing. One major focus of the workshop was massive parallelism, covering theory and models of computing, algorithm design and analysis, routing architectures and interconnection networks, languages, and application requirements. More conventional issues involving the design and use of parallel computers with a few dozen processors were not addressed at the meeting. A driving force behind the realization of this workshop was the need for interaction between theoreticians and practitioners of parallel computation. Therefore, a group of selected participants from the theory community was invited to attend, together with well-known colleagues actively involved in parallelism from national laboratories, government agencies, and industry.
More details
Edition
Softcover reprint of the original 1st ed. 1989
Language
English
Place of publication
NY
United States
Target group
Professional and scholarly
Illustrations
XI, 166 p.
Dimensions
Height: 28 cm
Width: 21.6 cm
ISBN-13
978-1-4613-9670-3 (9781461396703)
DOI
10.1007/978-1-4613-9668-0
Schweitzer Classification
Other editions
Additional editions
Jorge L.C. Sanz
Opportunities and Constraints of Parallel Computing
E-Book
12/2012
Springer
€82.38
Available for download
Book
10/1989
Springer
€85.55
Article exhausted; check different version
Content
A Critique of the PRAM Model of Computation.- Future Requirements for Effective Use of Parallel Computers.- A Perspective on Shared-memory and Message-memory Architectures.- Some Observations on Models of Parallel Computation.- The Physics of the Parallel Machines.- Parallel Program Design.- The APRAM: Incorporating Asynchrony into the PRAM Model.- Architectures for Data Parallel Algorithms.- Algorithm Design for Different Computer Architectures.- Neural Networks and Computer Science.- Theoretical Problems in the Design of Tools to Aid in the Construction of Parallel Programs.- Towards More Flexible Architectures.- Towards Better Shared Memory Programming Models.- New Cost Measures in Graph Embeddings.- Parallel Computing: Perspectives and Prospects.- Challenges in Multiprocessor Architectures.- Making Parallel Computers Usable: A Software Environment for Parallel Computer Vision.- A Position Paper on Parallel Computation.- Efficient Parallel Algorithms: Theory and Practice.- What is the Right Model for Designing Parallel Algorithms?.- Beyond Parallel Random-Access Machines.- Are Pointer-Based Parallel Algorithms Realistic?.- Opportunities and Constraints of Parallel Computing.- Adaptive Routing in Multicomputer Networks.- New Languages with Implicit Parallelism and Heap Storage are Needed for Parallel Programming.- Very High Level Parallel Programming.- A Case for Randomized Parallel Algorithms.- Designing and Using Parallel Architectures.- The Tower of Babel in Parallel Computing.- Why Are All Us Parallel Numerical Analysts Doing Parallel Software Tools?.- Portraying the Dynamics of Concurrent Programs.- Remarks on the Directions of Research in Parallel Computing.- Parallelism, Compiler Optimization, and Deterministic Scheduling Theory.- Time for the 4GLs?.- Scalable Shared Memory MIMD Computers.- Parallel Computation Models - Some Useful Questions.- Parallel Algorithms and Programming Languages.- Programming High Performance Parallel Machines.- Optimally Universal Parallel Computers.- Basic Research in Parallel Computing Must Address Both Short- and Long-Term Objectives.- PRAM Algorithms: Teach and Preach.- Too Much "Research" on Parallel Numerical Algorithms.