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.

Multicore Programming with OpenMP
Richard Brown; Elizabeth Shoop
In this lab, we will create a program that intentionally uses multi-core parallelism, upload and run it on the MTL, and explore the issues in parallelism and concurrency that arise. This module uses OpenMP.

Multi-core programming with Intel's Manycore Testing Lab (using Threading Building Blocks)
Professor Richard Brown, St. Olaf College
Intel Corporation has set up a special remote system that allows faculty and students to work with computers with lots of cores, called the Manycore Testing Lab (MTL). In this lab, we will create a program that intentionally uses multi-core parallelism, upload and run it on the MTL, and explore the issues in parallelism and concurrency that arise.

Concurrent Access to Data Structures in C++
Richard Brown
This module enables students to experiment with creating a task-parallel solution to the problem of crawling the web by using C++ with Boost threads and thread-safe data structures available in the Intel Threading ...

Pandemic Exemplar
Elizabeth Shoop
Sequential and parallel versions of a mote carlo simulation of the spread of infectious disease are presented in detail. Students can run the code and examine performance of sequential and parallel versions.

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.

Heterogeneous Computing
Elizabeth Shoop;
Message Passing Interface (MPI) is a programming model widely used for parallel programming in a cluster. NVIDIA®'s CUDA, a parallel computing platform and programming model, uses GPU for parallel computation problems. This module will explore ways to combine these two parallel computing platforms to make parallel computation more efficient.

Patternlets in Parallel Programming
Material originally created by Joel Adams, Calvin CollegeCompiled by Libby Shoop, Macalester College
Short, simple C programming examples of basic shared memory programming patterns using OpneMP and basic message-passing patterns using MPI.

Concept: Data Decomposition Pattern
Elizabeth Shoop
This module consists of reading material and code examples that depict the data decomposition pattern in parallel programming, using a small-sized example of vector addition (sometimes called the "Hello, World" of parallel programming.

Visualize Numerical Integration
Elizabeth Shoop
This is an activity with working code supplied that enables students to see how various forms of the data decomposition pattern map processing units to computations.



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