BIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel Computing
by Alan Kaminsky
Publisher: Rochester Institute of Technology 2015
Number of pages: 424
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.
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by G.C. Fox, R.D. Williams, P.C. Messina - 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.
by Blaise Barney - Lawrence Livermore National Laboratory
This tutorial covers the very basics of parallel computing, and is intended for someone who is just becoming acquainted with the subject. It begins with a brief overview, including concepts and terminology associated with parallel computing.
by Ian Parberry - Prentice Hall
The rapid growth of parallel complexity theory has led to a proliferation of parallel machine models. This book presents a unified theory of parallel computation based on a network model. It is the first such synthesis in book form.
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.