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Friday, December 06
Analysis of QMC Applications on Petascale ComputersJeongnim Kim,, Materials Science and Technology and Computer Science Research Groups, Oak Ridge, TN
Computer Science Research Group Seminar
1:00 PM — 2:00 PM, Building 5700, Room L-204
Contact: Cindy Sonewald (Sonewaldc@ornl.gov), 865.574.3125
AbstractContinuum Quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles. The multiple forms of parallelism afforded by QMC algorithms and the high compute-to-communication ratio make them ideal candidates for acceleration in the multi/many-core paradigm, as demonstrated by the performance of QMCPACK on various high-performance computing (HPC) platforms including Titan (Cray XK7) and Mira (IBM BlueGene Q). The changes expected on future architectures - orders of magnitude higher parallelism, hierarchical memory and communication, and heterogeneous nodes - pose great challenges to application developers but also present opportunities to transform them to tackle new classes of problems. This talk presents core QMC algorithms and their implementations in QMCPACK on the HPC systems of today. The speaker will discuss the performance of typical QMC workloads to elucidate the critical issues to be resolved for QMC to fully exploit increasing computing powers of forthcoming HPC systems.