Intel® Parallel Computing Center at Georgia Institute of Technology

Principal Investigators:

Edmond Chow is an Associate Professor in the School of Computational Science and Engineering at Georgia Institute of Technology. He previously held positions at D. E. Shaw Research and Lawrence Livermore National Laboratory. His research is in developing and applying numerical methods and high-performance computing to solve large-scale scientific computing problems. Dr. Chow was awarded the 2009 ACM Gordon Bell prize and the 2002 U.S. Presidential Early Career Award for Scientists and Engineers (PECASE). He serves or has served as Associate Editor for ACM Transactions on Mathematical Software and SIAM Journal on Scientific Computing.


The Intel® Parallel Computing Center (Intel® PCC) at Georgia Tech is working on modernizing the performance and functionality of software for multicore and manycore processors in the fields of computational chemistry and biochemistry. Both these fields very actively fuel scientific discovery in chemistry, biology, materials science, pharmacology, chemical physics, chemical engineering, and energy research, and are responsible for a significant portion of computer and supercomputer time worldwide. Advances in high-performance applications in these fields promise breakthroughs in solving challenging problems, including real-time and large-scale problems that cannot be solved today.

Work in the Intel PCC focuses on two computational problems that can make a wide impact in chemistry and biochemistry. The first problem is the calculation of electronic integrals, a computationally intensive step in every quantum chemistry code. Work is underway to develop a library for integral calculation optimized for Intel Many Integrated Core architecture, and easily integrated into quantum chemistry codes running on distributed and heterogeneous Intel Xeon® and Intel Xeon Phi™ coprocessor platforms. The second problem is the calculation of long-range forces in hydrodynamic N-body simulations, such as Brownian dynamics and Stokesian dynamics simulations of biological macromolecules. Software for simulations based on fast algorithms such as FMM and PME and designed to fully exploit the potential of today's processors will enable truly large-scale and long-timescale simulations and impact the type of science that can be performed.

Computer scientists need knowledge in applications and associated algorithms in order to make the greatest possible performance improvements in scientific codes. With this goal, the Intel PCC will develop curricular materials in computational chemistry and biochemistry accessible to computer science students, which can be used in courses combining applications and high-performance implementation.


Related Websites:

For more complete information about compiler optimizations, see our Optimization Notice.