Computer Science 374 - Parallel Computer Systems

Computing hardware today is a complex and highly diverse landscape, but one common thread is the prevalence and scale of parallel computation.  Scientific computing, generative AI, and other intensive modern computing tasks are made possible by rapidly evolving hardware capabilities, robust systems support, and effective programming.   Students in this course will engage in collaborative projects and analyze the key design choices, limitations, and capabilities of parallel computing systems, with an emphasis on GPU architecture and programming.  This course will expose students to essential models for parallel computation (for example: shared memory, message passing, and data-parallelism), as well as practical analysis of parallel computer architectures, through the development and optimization of parallel programs using prominent frameworks such as OpenMP and CUDA.

Requisite: COSC-171 or COSC-175 and COSC-211. Spring semester. Professor Pentecost.

How to handle overenrollment: Priority to majors.

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: Quantitative reasoning.