Distributed and Parallel ComputingThe state-of-the-art in high-performance concurrent computing -- theory and practice.-- Detailed coverage of the growing integration between parallel and distributed computing.-- Advanced approaches for programming distributed, parallel systems -- and adapting traditional sequential software.-- Creating a Parallel Virtual Machine (PVM) from networked, heterogeneous systems.This is the most up-to-date, comprehensive guide to the rapidly changing field of distributed and parallel systems.The book begins with an introductory survey of distributed and parallel computing: its rationale and evolution. It compares and contrasts a wide variety of approaches to parallelism, from distributed computer networks, to parallelism within processors (such as Intel's MMX), to massively parallel systems. The book introduces state-of-the-art methods for programming parallel systems, including approaches to reverse engineering traditional sequential software. It includes detailed coverage of the critical scheduling problem, compares multiple programming languages and environments, and shows how to measure the performance of parallel systems. The book introduces the Parallel Virtual Machine (PVM) system for writing programs that run on a network of heterogenous systems; the new Message Passing Interface (MPI-2)standard; and finally, the growing role of Java in writing distributed and parallel applications. |
Contents
What is distributed and parallel computing? | 1 |
Performance measures | 42 |
Distributed and parallel processors | 82 |
Copyright | |
12 other sections not shown
Common terms and phrases
active algorithm application architecture argument array assigned assume blocking body buff buffer called chapter client collective communication complexity components computing configuration connection Consider construct containing copy cost create define dependencies distributed distributed computing distributed system elements example execution existing figure four function given identifier illustrates increase initial input integer interface iteration Java loop machine matrix means measure memory method multiple node number of processors object operation optimal parallel parallel computing parameters performance PRAM problem processors provides rank receive result returns root scheduling sequential server shared shows single solve sort specified speed speedup started statement step supervisor Suppose synchronization takes task task graph tellers thread tion tree units variable vector wait workers write