by Wolfgang Merkle
Publisher: ESSLLI 2001
Number of pages: 46
The first part of the course gives an introduction to randomized algorithms and to standard techniques for their derandomization. The second part presents applications of the probabilistic method to the construction of logical models and briefly discusses related issues such as Rado-graphs and 0-1 laws.
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by Guy Blelloch - The MIT Press
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.
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A comprehensive treatment focusing on the creation of efficient data structures and algorithms, explaining how to select the data structure best suited to specific problems. It uses Java programming language and is suitable for second-year courses.