Parallel Algorithms in Scientific Computing
Explore the application of parallel algorithms in machine learning, graph analytics, and modeling and simulation. Examine high-performance computing, parallel non-numerical and numerical algorithms for shared and distributed memory architectures. Discuss examples including sorting, merging, searching, linear algebra, graph algorithms, KD-trees, and fast transforms. Explore theory, programming, and performance optimization and analysis. Computational Science, Engineering, and Mathematics 392 (Topic: Parallel Algors Scientfc Comp) and 392 (Topic 1) may not both be counted.
Prerequisites & course information
Explore the application of parallel algorithms in machine learning, graph analytics, and modeling and simulation. Examine high-performance computing, parallel non-numerical and numerical algorithms for shared and distributed memory architectures. Discuss examples including sorting, merging, searching, linear algebra, graph algorithms, KD-trees, and fast transforms. Explore theory, programming, and performance optimization and analysis. Computational Science, Engineering, and Mathematics 392 (Topic: Parallel Algors Scientfc Comp) and 392 (Topic 1) may not both be counted.
Sources
- Course catalogue ↗2026-2027