Algorithms and Parallel Computing

There is a software gap between the hardware potential and the performance that can be attained using today’s software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.

Table of Contents

Chapter 1: Introduction
Chapter 2: Enhancing Uniprocessor Performance
Chapter 3: Parallel Computers
Chapter 4: Shared-Memory Multiprocessors
Chapter 5: Interconnection Networks
Chapter 6: Concurrency Platforms
Chapter 7: Ad Hoc Techniques for Parallel Algorithms
Chapter 8: Nonserial–Parallel Algorithms
Chapter 9: z-Transform Analysis
Chapter 10: Dependence Graph Analysis
Chapter 11: Computational Geometry Analysis
Chapter 12: Case Study: One-Dimensional IIR Digital Filters
Chapter 13: Case Study: Two- and Three-Dimensional Digital Filters
Chapter 14: Case Study: Multirate Decimators and Interpolators
Chapter 15: Case Study: Pattern Matching
Chapter 16: Case Study: Motion Estimation for Video Compression
Chapter 17: Case Study: Multiplication over GF (2m)
Chapter 18: Case Study: Polynomial Division over GF(2)
Chapter 19: The Fast Fourier Transform
Chapter 20: Solving Systems of Linear Equations
Chapter 21: Solving Partial Differential Equations Using Finite Difference Method