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.
Home page url
Download or read it online for free here:
by Earl T. Campbell, Joseph Fitzsimons - arXiv
This review provides a gentle introduction to one-way quantum computing in distributed architectures. One-way quantum computation shows significant promise as a model for distributed systems, particularly probabilistic entangling operations.
by Nicholas Carriero, David Gelernter - 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.
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 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.