Logo

Programming on Parallel Machines

Small book cover: Programming on Parallel Machines

Programming on Parallel Machines
by

Publisher: University of California, Davis
Number of pages: 410

Description:
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.

Download or read it online for free here:
Download link
(2.5MB, PDF)

Similar books

Book cover: BIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel ComputingBIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel Computing
by - 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.
(1076 views)
Book cover: Parallel Computing Works!Parallel Computing Works!
by - 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.
(4777 views)
Book cover: Parallel Computing: Architectures, Algorithms and ApplicationsParallel Computing: Architectures, Algorithms and Applications
by - John von Neumann Institute for Computing
The book gives an overview of the developments, applications and future trends in high performance computing for all platforms. It addresses all aspects of parallel computing, including applications, hardware and software technologies.
(4903 views)
Book cover: Distributed Systems for Fun and ProfitDistributed Systems for Fun and Profit
by - 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.
(2461 views)