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 David M. Mount - University of Maryland
The focus is on how to design good algorithms, and how to analyze their efficiency. The text covers some preliminary material, optimization algorithms, graph algorithms, minimum spanning trees, shortest paths, network flows and computational geometry.
A data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Contents of the book: Sequences; Dictionaries; Sets; Priority queues; Successors and neighbors; Integer and string searching.
by Leonard Soicher, Franco Vivaldi - Queen Mary University of London
This text is a course in mathematical algorithms, intended for second year mathematics students. It introduces the algorithms for computing with integers, polynomials and vector spaces. The course requires no computing experience.
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.