Join Amazon Prime and ship Two-Day for free and Overnight for $3.99. Already a member? Sign in.
A Parallel Algorithm Synthesis Procedure for High-Perform... and over 190,000 other books are available for Amazon Kindle – Amazon’s new wireless reading device. Learn more

 

or
Sign in to turn on 1-Click ordering.
 
   
More Buying Choices
31 used & new from $61.75

Have one to sell? Sell yours here
 
   
A Parallel Algorithm Synthesis Procedure for High-Performance Computer Architecture (Series in Computer Science)
 
 
Start reading A Parallel Algorithm Synthesis Procedure for High-Perform... on your Kindle in under a minute.

Don’t have a Kindle? Get yours here.
 
  

A Parallel Algorithm Synthesis Procedure for High-Performance Computer Architecture (Series in Computer Science) (Hardcover)

by Ian N. Dunn (Author), Gerard G.L. Meyer (Author) "Parallel computing is the only viable, cost-effective approach to meeting the timing constraints of many high performance signal processing applications..." (more)
Key Phrases: hierarchy parameterization, concurrency sets, task dependency graph, Parallel Algorithm Synthesis Procedure, Parallel Compact, Cray Research (more...)
No customer reviews yet. Be the first.

List Price: $175.00
Price: $175.00 & this item ships for FREE with Super Saver Shipping. Details
Upgrade this book for $35.00 more, and you can read, search, and annotate every page online. See details
In Stock.
Ships from and sold by Amazon.com. Gift-wrap available.

Only 1 left in stock--order soon (more on the way).

Want it delivered Monday, December 8? Choose One-Day Shipping at checkout. See details

Ordering for Christmas? To ensure delivery by December 24, choose FREE Super Saver Shipping at checkout. Read more about holiday shipping.

20 new from $110.90 11 used from $61.75
Also Available in: List Price: Our Price: Other Offers:
Kindle Edition (Kindle Book) $140.00
 
   

Editorial Reviews

Product Description
Despite five decades of research, parallel computing remains an exotic, frontier technology on the fringes of mainstream computing. Its much-heralded triumph over sequential computing has yet to materialize. This is in spite of the fact that the processing needs of many signal processing applications continue to eclipse the capabilities of sequential computing. The culprit is largely the software development environment. Fundamental shortcomings in the development environment of many parallel computer architectures thwart the adoption of parallel computing. Foremost, parallel computing has no unifying model to accurately predict the execution time of algorithms on parallel architectures. Cost and scarce p