Survey of Parallel Electronic Structure Developments

We now describe a subset of all work done to parallelize electronic structure methods. The remainder of this section provides an outline of the work significant in the development of state-of-the-art electronic structure algorithms and codes. When appropriate, we focus on the algorithm and performance of applications. 

Shared-memory parallel processing was certainly more successful for QC in earlier applications and continues to play a significant role in high performance computational chemistry. A coarse-grained parallel implementation scheme for the direct SCF method by Liithi et al. allowed for a near-asymptotic speed-up involving a very low parallelization overhead without compromising the vector performance of vector-parallel architectures. 

Wilson and co-workers conducted a series of experiments in vector and parallel processing based on the diagrammatic many-body perturbation theory (MBPT). Moncrieff, Baker, and Wilson described an efficient evaluation of 

Finally, as an example of a more empirical application, we draw attention to the vector and parallel FCI algorithm of Bendazzoli and Evangelisti.i The algorithm described was integral driven and was based on the explicit construction of tables that realized the correspondence between the FCI vector x and the product vector Hx, H being the Hamiltonian matrix of the system. In this way no decomposition of the identity was needed, and in the simplest implementation only the two vectors x and Hx need to be stored on disk. The main test was 

Before embarking on a detailed account of the work to date in parallelizing QC codes at both the Hartree—Fock and post-Hartree—Fock levels, we draw attention to work that describes the provision of general parallel computational chemistry capabilities. 

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