Is Parallel Programming Hard, And, If So, What Can You Do About It?
by Paul E. McKenney
Number of pages: 413
The purpose of this book is to help you understand how to program shared-memory parallel machines without risking your sanity. By describing the algorithms and designs that have worked well in the past, we hope to help you avoid at least some of the pitfalls that have beset parallel projects.
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by Dimitri P. Bertsekas, John Tsitsiklis - 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.
by Henri Casanova, et al. - CRC Press
This book provides a rigorous yet accessible treatment of parallel algorithms, including theoretical models of parallel computation, parallel algorithm design for homogeneous and heterogeneous platforms, complexity and performance analysis, etc.
by Sergey A. Babkin - CreateSpace
This book provides an advanced guide to the issues of the parallel and multithreaded programming. It goes beyond the high-level design of the applications, into the details that are often overlooked but vital to make the programs work.
by Norm Matloff - University of California, Davis
This book is aimed more on the practical end of things, real code is featured throughout. The emphasis is on clarity of the techniques and languages used. It is assumed that the student is reasonably adept in programming and linear algebra.