Parallel Computing in the Computer Science Curriculum > Modules

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GPU Programming
Elizabeth Shoop; Yu Zhao
In this module, we will learn how to create programs that intensionally use GPU to execute. To be more specific, we will learn how to solve parallel problems more efficiently by writing programs in CUDA C Programming Language and then executes them on GPUs based on CUDA architecture.

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.

Timing Operations in CUDA
Joel Adams, Calvin College, and Jeffrey Lyman, Macalester College
Through completion of Vector Addition, multipliction, square root, and squaring programs, students will gain an understanding of when the overhead of creating threads and copying memory is worth the speedup of GPU coding.



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