EC EN 528
High Performance Parallel Computing
Electrical and Computer Engineering
Ira A. Fulton College of Engineering
Course Description
Explore GPU, multi-core and distributed architectures. Programming topics include forms of parallelism, decomposition, scaling issues, data locality, computation patterns, parallel libraries, languages, and performance analysis. Parallel application examples illustrate design principles and potential performance benefits.
When Taught
Fall
Grade Rule
Standard Grade Rule: A B C D E I
Min
3
Fixed
3
Fixed
3
Fixed
2
Other Prerequisites
EC En 330 or equivalent.
Recommended
Strong programming skills are required with exposure to C/C++.
Title
Architecture
Learning Outcome
Ability to compare and contrast parallel computing architectures (GPU, SMP, cluster…).
Title
Programming models, libraries
Learning Outcome
Ability to write performant software using common parallel computation patterns (vector, matrix, convolution, stencil…).
Title
Application examples
Learning Outcome
Acquire a practical knowledge of how parallelism is used effectively in a few application examples (design principles).
Title
Labs
Learning Outcome
Ability to apply benchmarking techniques and profiling tools to analyze application performance (optimization).
