Vector Models for Data-Parallel Computing
by Guy Blelloch
Publisher: The MIT Press 1990
Number of pages: 268
Vector Models for Data-Parallel Computing describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It presents many algorithms based on the model, ranging from graph algorithms to numerical algorithms, and argues that data-parallel models are not only practical and can be applied to a surprisingly wide variety of problems, they are also well suited for very-high-level languages and lead to a concise and clear description of algorithms and their complexity.
Home page url
Download or read it online for free here:
by K. Raghava Rao - Smashwords
This book provides a complete information to the modern study of computer algorithms. It presents many concepts in a considerable depth, so that it can be understand by all levels of readers. Each and every concept is explained by suitable examples.
by Chris Okasaki - Carnegie Mellon University
This book describes data structures from the point of view of functional languages. The author includes both classical data structures, such as red-black trees, and a host of new data structures developed exclusively for functional languages.
by Sean Luke
This is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other non-experts. It was developed as a series of lecture notes for an undergraduate course.
by Clifford A. Shaffer - Virginia Tech
A comprehensive treatment of fundamental data structures and algorithm analysis with a focus on how to create efficient data structures and algorithms. Aims to help the reader gain an understanding of how to select or design the best data structure.