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Scalable, Fine Grain, Parallelization of the Car-Parrinello ab initio Molecular Dynamics Method
PPL Technical Report 2005
Publication Type: Paper
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Many important problems in material science, chemistry, solid-state physics, and biophysics necessitate a first principles or ab initio based molecular modeling approach. That is, atomic forces generated from an energy function that explicitly includes electrons are required to explore non-trivial, technologically interesting systems. A first principles technique that has proved to be particularly efficient and useful is the {\em Car-Parrinello ab initio molecular dynamics method} (CPAIMD). This computationally intensive method which is typically applied to study systems containing 100-1000s of atoms, has resisted attempts to achieve parallel scaling beyond processor numbers equal to the number of electronic states (100-1000 processors in system sizes of interest). Indeed, CPAIMD computations involve a large number of phases with complex dependencies, that lead to difficult communication optimization and load balancing problems. These phases include multiple concurrent sparse 3D-Fast-Fourier Transform(3D-FFT) computations, non-square matrix multiplies and few concurrent dense 3D-FFT computations. Using Charm++ and the concept of virtualization, the CPAIMD phases are discretized into a large number of virtual processors which are, in turn, mapped flexibly onto physical processors by the Charm++ runtime system and dynamically adjusted to achieve high performance. A benchmark with 32 water molecules (128 states) scaling to more than 1000 processors is given, setting a precedent for this problem.
Sameer Kumar and Yan Shi and Eric Bohm and L. V. Kale, "Scalable, fine grain, parallelization of the Car-Parrinello ab initio molecular dynamics method", UIUC, Dept. of Computer Science, 2005.
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