CS 607 - Parallel Computing

Units: 3
Parallel Computing principles and programming techniques. Topics may include: parallel architectures, cluster systems, message passing interfaces, GPU programming, MapReduce, shared-memory, and parallel storage systems. Design and implementation computing frameworks and evaluation of performance efficiency. Programming projects and literature review.

Prerequisites: CS 421 or CS 621 and CS 321.
Credit Restrictions: Computer Science M.S. or B.S. students only.

Possible Instructional Methods: Entirely On-ground.
Grading: A-F grading only.
Student Learning Outcomes - Upon successful completion of this course students will be able to:

Formulate decomposition methodologies for the parallel programming development.
Explain load balancing issues for parallel programs.
Analyze parallel architectures and the effect of architecture on the implementation and design of a parallel algorithm.
Examine the quantifying speedup, empirical tools and theoretical models of parallel architectures.
Determine computational bottlenecks and optimize the performance of parallel programs.