- Author:
- Steven Brawer
No abstract available.
Cited By
- Huang F, Tie B, Tao J, Tan X and Ma Y (2020). Methodology and optimization for implementing cluster-based parallel geospatial algorithms with a case study, Cluster Computing, 23:2, (673-704), Online publication date: 1-Jun-2020.
- Huang F, Tao J, Xiang Y, Liu P, Dong L and Wang L (2017). Parallel compressive sampling matching pursuit algorithm for compressed sensing signal reconstruction with OpenCL, Journal of Systems Architecture: the EUROMICRO Journal, 72:C, (51-60), Online publication date: 1-Jan-2017.
Alonso G, Blott S, Fessler A and Schek H Correctness and parallelism in composite systems Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems, (197-208)- Yan Y, Zhang X and Ma Q (1997). Software Support for Multiprocessor Latency Measurement and Evaluation, IEEE Transactions on Software Engineering, 23:1, (4-16), Online publication date: 1-Jan-1997.
- Shirai K and Hiwatashi J A design system for special purpose processors based on architectures for distributed processing Proceedings of the conference on European design automation, (380-385)
- Hartman J and Sanders D (1991). Teaching a course in parallel processing with limited resources, ACM SIGCSE Bulletin, 23:1, (97-101), Online publication date: 1-Mar-1991.
- Hartman J and Sanders D Teaching a course in parallel processing with limited resources Proceedings of the twenty-second SIGCSE technical symposium on Computer science education, (97-101)
- Hanson F A real introduction to supercomputing Proceedings of the 1990 ACM/IEEE conference on Supercomputing, (376-385)
- Sanders D and Hartman J Getting started with parallel programming Proceedings of the twenty-first SIGCSE technical symposium on Computer science education, (86-88)
- Sanders D and Hartman J (1990). Getting started with parallel programming, ACM SIGCSE Bulletin, 22:1, (86-88), Online publication date: 1-Feb-1990.
Index Terms
- Introduction to parallel programming
Reviews
Ryszard Janicki
This elementary and practical introduction to parallel programming is divided into 15 chapters: Introduction Tiny Fortran Hardware and Operating System Models Processes, Shared Memory, and Simple Parallel Programs Basic Parallel Programming Techniques Barriers and Race Conditions Introduction to Scheduling—Nested Loops Overcoming Data Dependencies Scheduling Summary Linear Recurrence Relations—Backward Dependencies Performance Tuning Discrete Event, Discrete Time Simulation Some Applications Semaphores and Events Programming Projects Most basic concepts, such as the creation of multiple processes, memory sharing, scheduling, and data dependencies, are covered and illustrated by examples in simplified FORTRAN. The book also presents a number of applications, such as a discrete-time, discrete-event simulator, numerical integration, Gaussian elimination, a parallel version of the traveling salesman problem, and the exploration of a maze. Unfortunately, the majority of the more advanced results and techniques (particularly the theoretical ones) are not mentioned. Still, Brawer has written a very good text for beginners (that is, programmers and researchers with no previous exposure to parallel programming).
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