Parallel Computing in the Computer Science Curriculum > Modules


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Concurrent Access to Data Structures
Professor Libby Shoop, Macalester College
This module enables students to experiment with creating a task-parallel solution to the problem of crawling the web by using Java threads and thread-safe data structures available in the java.util.concurrent package.

Concurrency and Map-Reduce Strategies in Various Programming Languages
Professor Richard Brown, St. Olaf College
This concept module explores how concurrency and parallelism have been established in programming languages and how one can implement map-reduce in several high-level programming languages taught in a CS curriculum, including Scheme, C++, Java, and Python.

Map-reduce Computing for Introductory Students using WebMapReduce
Professor Richard Brown, St. Olaf College Professor Libby Shoop, Macalester College
This module emphasizes data-parallel problems and solutions, the so-called 'embarrassingly parallel' problems where processing of input data can easily be split among several parallel processes. Students use a web application called WebMapReduce (WMR) to write map and reduce functions that operate on portions of a massive dataset in parallel.

Drug Design Exemplar
Richard Brown
An important problem in the biological sciences is that of drug design: finding small molecules, called ligands, that are good candidates for use as drugs. We introduce the problem and provide several different parallel solutions, in the context of parallel program design patterns.

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