Education and research challenges in parallel computing

Over three decades of parallel computing, new computational requirements and systems have steadily evolved, yet parallel software remains notably more difficult relative to its sequential counterpart, especially for fine-grained parallel applications. We discuss the role of education to address challenges posed by applications such as informatics, scientific modeling, enterprise processing, and numerical computation. We outline new curricula both in computational science and in computer science. There appear to be new directions in which graduate education in parallel computing could be directed toward fulfilling needs in science and industry.