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 Mark Anthony McLaughlin - arXiv
Internet distributed applications (IDAs) are internet applications with which many users interact simultaneously. In this paper the author provides a basis for a framework that combines IDAs collectively within a single context.
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 Sergio Barbarossa, Stefania Sardellitti, Paolo Di Lorenzo - arXiv
We consider the problems of distributed detection and estimation in wireless sensor networks. We provide a general framework aimed to show how an efficient design of a sensor network requires a joint organization of in-network communication.
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.