Curtis L Janssen | PubMed Health

PubMed2004

Component-based integration of chemistry and optimization software.

Typical scientific software designs make rigid assumptions regarding programming language and data structures, frustrating software interoperability and scientific collaboration. Component-based software engineering is an emerging approach to managing the increasing complexity of scientific software. Component technology facilitates code interoperability and reuse. Through the adoption of methodology and tools developed by the Common Component Architecture Forum, we have developed a component architecture for molecular structure optimization. Using the NWChem and Massively Parallel Quantum Chemistry packages, we have produced chemistry components that provide capacity for energy and energy derivative evaluation. We have constructed geometry optimization applications by integrating the Toolkit for Advanced Optimization, Portable Extensible Toolkit for Scientific Computation, and Global Arrays packages, which provide optimization and linear algebra capabilities. We present a brief overview of the component development process and a description of abstract interfaces for chemical optimizations. The components conforming to these abstract interfaces allow the construction of applications using different chemistry and mathematics packages interchangeably. Initial numerical results for the component software demonstrate good performance, and highlight potential research enabled by this platform.

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PubMed2004

Second-order Møller-Plesset theory with linear R12 terms (MP2-R12) revisited: auxiliary basis set method and massively parallel implementation.

Ab initio electronic structure approaches in which electron correlation explicitly appears have been the subject of much recent interest. Because these methods accelerate the rate of convergence of the energy and properties with respect to the size of the one-particle basis set, they promise to make accuracies of better than 1 kcal/mol computationally feasible for larger chemical systems than can be treated at present with such accuracy. The linear R12 methods of Kutzelnigg and co-workers are currently the most practical means to include explicit electron correlation. However, the application of such methods to systems of chemical interest faces severe challenges, most importantly, the still steep computational cost of such methods. Here we describe an implementation of the second-order Møller-Plesset method with terms linear in the interelectronic distances (MP2-R12) which has a reduced computational cost due to the use of two basis sets. The use of two basis sets in MP2-R12 theory was first investigated recently by Klopper and Samson and is known as the auxiliary basis set (ABS) approach. One of the basis sets is used to describe the orbitals and another, the auxiliary basis set, is used for approximating matrix elements occurring in the exact MP2-R12 theory. We further extend the applicability of the approach by parallelizing all steps of the integral-direct MP2-R12 energy algorithm. We discuss several variants of the MP2-R12 method in the context of parallel execution and demonstrate that our implementation runs efficiently on a variety of distributed memory machines. Results of preliminary applications indicate that the two-basis (ABS) MP2-R12 approach cannot be used safely when small basis sets (such as augmented double- and triple-zeta correlation consistent basis sets) are utilized in the orbital expansion. Our results suggest that basis set reoptimization or further modifications of the explicitly correlated ansatz and/or standard approximations for matrix elements are necessary in order to make the MP2-R12 method sufficiently accurate when small orbital basis sets are used. The computer code is a part of the latest public release of Sandia's Massively Parallel Quantum Chemistry program available under GNU General Public License.

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