Logo

Parallel Complexity Theory by Ian Parberry

Small book cover: Parallel Complexity Theory

Parallel Complexity Theory
by

Publisher: Prentice Hall
ISBN/ASIN: 0273087835
ISBN-13: 9780273087830
Number of pages: 212

Description:
Parallel complexity theory is one of the fastest-growing fields in theoretical computer science. This rapid growth has led to a proliferation of parallel machine models and theoretical frameworks. This book presents a unified theory of parallel computation based on a network model.

Download or read it online for free here:
Download link
(8.6MB, PDF)

Similar books

Book cover: How to Write Parallel Programs: A First CourseHow to Write Parallel Programs: A First Course
by - MIT Press
In the near future every programmer will need to understand parallelism, a powerful way to run programs fast. The authors of this straightforward tutorial provide the instruction that will transform ordinary programmers into parallel programmers.
(9692 views)
Book cover: Parallel Computing Works!Parallel Computing Works!
by - Morgan Kaufmann Publishers
A clear illustration of how parallel computers can be successfully applied to large-scale scientific computations. The book demonstrates how various applications in physics, biology and other sciences were implemented on real parallel computers.
(10233 views)
Book cover: Parallel and Distributed Computation: Numerical MethodsParallel and Distributed Computation: Numerical Methods
by - Athena Scientific
This is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the issues associated with such algorithms.
(11475 views)
Book cover: BIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel ComputingBIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel Computing
by - Rochester Institute of Technology
With the book BIG CPU, BIG DATA, my goal is to teach you how to write parallel programs that take full advantage of the vast processing power of modern multicore computers, compute clusters, and graphics processing unit (GPU) accelerators.
(7160 views)