CS 7172:Parallel and Distributed Computing

3 Class Hours 0 Laboratory Hours 3 Credit Hours
This course covers various aspects of parallel and distributed processing and algorithm design with an emphasis on programming. Topics include: Taxonomy of parallel architectures; Shared-memory vs. message-passing architectures; Computation models and Performance metrics; Parallel/distributed algorithm design - basic techniques; Parallel/distributed programming techniques and issues: partitioning, load balancing, synchronization, task scheduling, message overheads, etc.; Parallel/distributed algorithms for sorting, matrices, etc.; Debugging, Profiling, and Performance enhancements of parallel and distributed programs. Students will gain experience in parallel and distributed programming on state-of-the-art cluster and GPGPU/CUDA machines, including a 700+ CUDA machine.