Programming on Parallel Machines
by Norm Matloff
Publisher: University of California, Davis 2012
Number of pages: 410
This is aimed more on the practical end of things, real code is featured throughout. The primary emphasis is on simplicity and clarity of the techniques and languages used. It is assumed that the student is reasonably adept in programming, and has math background through linear algebra.
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by Alan Kaminsky - Rochester Institute of Technology
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.
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.
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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.
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A tutorial of Erlang, a concurrent, functional programming language. The emphasis of this book is on learning through example and a number of well known problems in designing and programming concurrent fault-tolerant real-time systems.