Offered: Fall 2025 (current)
This course explores the design, analysis, and implementation of parallel algorithms for modern computing architectures, including multicore CPUs and GPUs. Students will learn to tackle computational challenges by leveraging parallelism at scale. The course balances theoretical rigor with practical implementation, emphasizing performance optimization, scalability, and emerging trends.
The core objectives of this course are to:
Design and analyze cost-optimal parallel algorithms for diverse architectures.
Implement parallel solutions using frameworks like CUDA, MPI, and OpenMP.
Diagnose bottlenecks in parallel systems (e.g., contention, communication overhead).
Evaluate research papers and industry trends in parallel computing.
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