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.
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by Ian Craw, John Pulham - University of Aberdeen
This course studies computer algorithms, their construction, validation and effectiveness. A number of topics will be covered: a general introduction to the subject, the problem of sorting data sets into order, the theory of formal grammars, etc.
by Robert Sedgewick, Kevin Wayne - Addison-Wesley Professional
This textbook surveys the most important algorithms and data structures in use today. Applications to science, engineering, and industry are a key feature of the text. We motivate each algorithm by examining its impact on specific applications.
by Jeff Erickson - University of Illinois at Urbana-Champaign
These are lecture notes, homework questions, and exam questions from algorithms courses the author taught at the University of Illinois. It is assumed that the reader has mastered the material covered in the first 2 years of a typical CS curriculum.
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The book shows how some computer algorithms can simplify complex summations and if there is no such simplification they will prove this to be the case. The authors present the underlying mathematical theory, and the principle theorems and proofs.