Study of parallel computing principles, architectures, and technologies; and parallel application development, performance, and scalability. Designed to help prepare students to formulate and develop parallel algorithms to implement effective applications for parallel computing systems. Three lecture hours a week for one semester. Statistics and Data Sciences 374C and Statistics and Scientific Computation 374C may not both be counted. Prerequisite: Mathematics 408D or 408M, 340L, and prior programming experience using C or Fortran on Linux or Unix systems.