Abstract
We present a hybrid OpenMP/Charm++ framework for solving the Self-Consistent-Field eigenvalue problem with parallelism in the strong scaling regime, , where is the number of cores, and a measure of system size, i.e. the number of matrix rows/columns, basis functions, atoms, molecules, etc. This result is achieved with a nested approach to Spectral Projection and the Sparse Approximate Matrix Multiply [Bock and Challacombe, SIAM J.~Sci.~Comput. 35 C72, 2013], and involves a recursive, task-parallel algorithm, often employed by generalized -Body solvers, to occlusion and culling of negligible products in the case of matrices with decay. Employing classic technologies associated with generalized -Body solvers, including over-decomposition, recursive task parallelism, orderings that preserve locality, and persistence-based load balancing, we obtain scaling beyond hundreds of cores per molecule for small water clusters ([HO], , ) and find support for an increasingly strong scalability with increasing system size .
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