A Novel Approach to Parallel Coupled Cluster Calculations:  Combining Distributed and Shared Memory Techniques for Modern Cluster Based Systems

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2007-05-01
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Olson, Ryan
Bentz, Jonathan
Kendall, Ricky
Schmidt, Michael
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Computer Science

Computer Science—the theory, representation, processing, communication and use of information—is fundamentally transforming every aspect of human endeavor. The Department of Computer Science at Iowa State University advances computational and information sciences through; 1. educational and research programs within and beyond the university; 2. active engagement to help define national and international research, and 3. educational agendas, and sustained commitment to graduating leaders for academia, industry and government.

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The Computer Science Department was officially established in 1969, with Robert Stewart serving as the founding Department Chair. Faculty were composed of joint appointments with Mathematics, Statistics, and Electrical Engineering. In 1969, the building which now houses the Computer Science department, then simply called the Computer Science building, was completed. Later it was named Atanasoff Hall. Throughout the 1980s to present, the department expanded and developed its teaching and research agendas to cover many areas of computing.

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1969-present

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Chemistry

The Department of Chemistry seeks to provide students with a foundation in the fundamentals and application of chemical theories and processes of the lab. Thus prepared they me pursue careers as teachers, industry supervisors, or research chemists in a variety of domains (governmental, academic, etc).

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The Department of Chemistry was founded in 1880.

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A parallel coupled cluster algorithm that combines distributed and shared memory techniques for the CCSD(T) method (singles + doubles with perturbative triples) is described. The implementation of the massively parallel CCSD(T) algorithm uses a hybrid molecular and “direct” atomic integral driven approach. Shared memory is used to minimize redundant replicated storage per compute process. The algorithm is targeted at modern cluster based architectures that are comprised of multiprocessor nodes connected by a dedicated communication network. Parallelism is achieved on two levels:  parallelism within a compute node via shared memory parallel techniques and parallelism between nodes using distributed memory techniques. The new parallel implementation is designed to allow for the routine evaluation of mid- (500−750 basis function) to large-scale (750−1000 basis function) CCSD(T) energies. Sample calculations are performed on five low-lying isomers of water hexamer using the aug-cc-pVTZ basis set.

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The following article appeared in Journal of Chemical Theory and Computation 3 (2007): and may be found at doi:10.1021/ct600366k.

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Mon Jan 01 00:00:00 UTC 2007
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