Enabling NAMD for Intel Xe
NAMD is a prominent parallel molecular dynamics application designed for high performance computing of large biomolecular systems. This session focuses on the development of NAMD for Intel GPUs using oneAPI/DPC++ by porting the efficient NAMD CUDA implementation and improving it with flexible vectorization for portable performance. We will also discuss the implementation in NAMD of relative debugging techniques across architectures and programming languages.
Speaker(s)
David Hardy
David Hardy is a senior research programmer at the University of Illinois at Urbana-Champaign. He leads the development of NAMD and was part of the research effort awarded in 2020 the ACM Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research.
Tareq Malas
Tareq joined Intel after his postdoctoral fellowship in Lawrence Berkeley National Laboratory under the NERSC Exascale Science Applications Program. He obtained his MS and Ph.D. degrees from King Abdullah University of Science and Technology (KAUST), in Saudi Arabia, advised by Prof. David Keyes in the Extreme Computing Research Center. His main areas of research are High Performance Computing in stencil computations and molecular dynamics simulations. He is interested in developing efficient high-performance computing algorithms on contemporary and future architectures for the most demanding applications. He likes to work near the CPU, as he did his Stencil code generation project in performing efficient vectorization in the CPU of the PowerPC 450 processor of the Blue Gene/P supercomputer. He worked on developing novel cache blocking techniques for reducing the data movement in the processor’s memory hierarchy, allowing the use of cache blocks that can efficiency span multiple cache domains. This work was developed in his Girih project for Intel® CPU. He is currently working on the performance optimizations of molecular dynamics simulations.
