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 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.
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 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.
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.