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 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 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 Al Geist, at al. - The MIT Press
Written by the team that developed the software, this tutorial is the definitive resource for scientists, engineers, and other computer users who want to use PVM to increase the flexibility and power of their high-performance computing resources.
by Mikito Takada - mixu.net
This text provides a more accessible introduction to distributed systems. The book brings together the ideas behind many of the more recent distributed systems - such as Amazon's Dynamo, Google's BigTable and MapReduce, Apache's Hadoop and so on.