With the stagnation of computer processor frequency due to the constraints of power and density, processor manufacturers are introducing additional parallelism within their designs to attain increased performance for highly parallel applications. The Intel Many Integrated Core (Intel MIC) architecture offers potential advantages over the current generation of heterogeneous architectures. To explore the effectiveness of the Intel MIC architecture on a broad range of computational science research, this award to the University of Tennessee Knoxville will (1) operate an experimental cluster equipped with Intel MIC co-processors for a period of two years and (2) coordinate an associated research program in collaboration with other institutions aimed at exploring the potential impact of the Intel MIC architecture and related programming models on key scientific codes. Through a partnership with Intel, the experimental cluster will initially be equipped with pre-release hardware to allow leading scientists and engineers in a variety of disciplines to begin working with the Intel MIC architecture prior to its commercial debut. The pre-release hardware will be upgraded to commercially available Intel MIC co-processors upon their release. The associated research program will be comprised initially of software projects (from the fields of plasma physics, nanoelectronics, astrophysics, chemistry, biology, quantum chromodynamics, and computer science) directly supported by this project and subsequently expanded to a more diverse set of scientific applications (selected by a panel of experts) proposed by research teams across the country in response to an open call for participation. These software projects will optimize important scientific and engineering applications using techniques that are expected to benefit performance on both conventional and accelerator-based architectures. Results will be made available publicly.
This project strategically promotes the use of emerging developments in accelerator hardware and parallel programming models within the nation's research community. The associated software projects are expected to advance the state of the art, positioning the nation's research community for future scientific and engineering advances. It also deepens the collaboration of the University of Tennessee Knoxville with industry. Finally, associated engagement activities that leverage existing University educational outreach programs ensure that the benefits of this research are broadly disseminated throughout the open science community and offer opportunities for traditionally underrepresented groups to participate in world-class computational research.
