Upon successful completion of this course, the student will be able to understand the concepts underlying distributed systems; analyze problems to identify performance bottlenecks, parallelization opportunities and concurrency issues in a distributed environment; create distributed and scalable implementations using multiple hosts/GPUs; design and implement algorithms using Hadoop, Spark and CUDA.
Prerequisites: Enrollment restricted to students with graduate standing in computer science or related discipline or acceptance into five-year accelerated program in computer science. The course will assume undergraduate-level background in algorithms, data structures and parallel programming.
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Dr. Gregory Triplett • Ph: (804) 828-5387 • firstname.lastname@example.org