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SCHEDULE: NOV 15-20, 2015

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Efficient Implementation of Quantum Materials Simulations on Distributed CPU-GPU Systems

SESSION: Applications: Material Science

EVENT TYPE: Papers, Best Paper Finalists

EVENT TAG(S): Applications

TIME: 11:30AM - 12:00PM

SESSION CHAIR(S): Suzanne Shontz

AUTHOR(S):Raffaele Solcà, Anton Kozhevnikov, Azzam Haidar, Stanimire Tomov, Jack Dongarra, Thomas C. Schulthess



We present a scalable implementation of the Linearized Augmented Plane Wave method for distributed memory systems, which relies on an efficient distributed, block-cyclic setup of the Hamiltonian and overlap matrices and allows us to turn around highly accurate 1000+ atom all-electron quantum materials simulations on clusters with a few hundred nodes. The implementation runs efficiently on standard multi-core CPU nodes, as well as hybrid CPU-GPU nodes. Key for the latter is a novel algorithm to solve the generalized eigenvalue problem for dense, complex Hermitian matrices on distributed hybrid CPU-GPU systems. Performance test for Li-intercalated CoO$_2$ supercells containing 1501 atoms demonstrate that high-accuracy, transferable quantum simulations can now be used in throughput materials search problems. A systematic comparison between our new hybrid solver and the ELPA2 library shows that the hybrid CPU-GPU architecture is considerably more energy efficient than traditional multi-core CPU only systems for such complex applications.

Chair/Author Details:

Suzanne Shontz (Chair) - University of Kansas|

Raffaele Solcà - ETH Zurich

Anton Kozhevnikov - Swiss National Supercomputing Center

Azzam Haidar - University of Tennessee, Knoxville

Stanimire Tomov - University of Tennessee, Knoxville

Jack Dongarra - University of Tennessee, Knoxville

Thomas C. Schulthess - Swiss National Supercomputing Center

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society