High Performance Computing for Science and Engineering
Harvard Extension School
CSCI E-205
Section 1
CRN 27108
As manufacturing processes approach the physical limits of transistor density, efficient code must exploit parallelism to scale with available computing resources. Scientific software developers must therefore adopt a think-parallel mindset to solve complex problems across academia, industry, and society. This course introduces parallel programming and its relationship to computer architectures, with an emphasis on high performance computing. Students develop experience with programming models such as OpenMP, MPI, and CUDA.
Credits: 4
View Tuition InformationTerm
Spring Term 2027
Part of Term
Full Term
Format
Online
Credit Status
Graduate
Section Status
Open