Distributed and grid computing principles and technologies. Covers common modes of grid computing for scientific applications, developing grid-enabled applications, and future trends in grid computing. Three lecture hours a week for one semester. Statistics and Data Sciences 394D and Statistics and Scientific Computation 394D may not both be counted. Prerequisite: Graduate standing, a third-semester calculus course or the equivalent, a linear algebra course or a matrices course, and prior programming experience using C or Fortran on Linux or Unix systems.