Parallelism in computational chemistry (original) (raw)
Related papers
Parallelism in computational chemistry: Applications in quantum and statistical mechanics
Physica B+C, 1985
Often very fundamental biochemical and biophysical problems defy simulations because of limitation in today's computers. We present and discuss a distributed system composed of two IBM-4341 and one IBM-4381, as front-end processors, and ten FPS-164 attached array processors. This parallel system-called LCAP-has presently a peak performance of about 120 MFlops; extensions to higher performance are discussed. Presently, the system applications use a modified version of VM/SP as the operating system: description of the modifications is given. Three applications programs have migrated from sequential to parallel; a molecular quantum mechanical, a Metropolis-Monte Carlo and a Molecular Dynamics program. Descriptions of the parallel codes are briefly outlined. As examples and tests of these applications we report on a study for proton tunneling in DNA base-pairs, very relevant to spontaneous mutations in genetics. As a second example, we present a Monte Carlo study of liquid water at room temperature where not only two-and three-body interactions are considered but-for the first time-also four-body interactions are included. Finally we briefly summarize a molecular dynamics study where two-and three-body interactions have been considered. These examples, and very positive performance comparison with today's supercomputers allow us to conclude that parallel computers and programming of the type we have considered, represent a pragmatic answer to many computer intensive problems.
High-performance computing in chemistry: NW Chem
Future Generation Computer Systems, 1996
Over the last three decades the methods of quantum chemistry have shown an impressive development: a large number of reliable and efficient approximations to the solution of the non-relativistic Schrödinger and the relativistic Dirac equation, respectively, are available. This is complemented by the availability of a number of well-developed computer programs which allow of the treatment of chemical problems as a matter of routine. This progress has been acknowledged by the Nobel prize in chemistry 1998 to John Pople and Walter Kohn for the development of quantum chemical methods.
Toward high‐performance computational chemistry: II. A scalable self‐consistent field program
Journal of Computational Chemistry, 1996
Several parallel algorithms for Fock matrix construction are described. The algorithms calculate only the unique integrals, distribute the Fock and density matrices over the processors of a massively parallel computer, use blocking techniques to construct the distributed data structures, and use clustering techniques on each processor to maximize data reuse. Algorithms based on both square and row-blocked distributions of the Fock and density matrices are described and evaluated. Variants of the algorithms are discussed that use either triple-sort or canonical ordering of integrals, and dynamic or static task clustering schemes. The algorithms are shown to adapt to screening, with communication volume scaling down with computation costs. Modeling techniques are used to characterize algorithm performance. Given the characteristics of existing massively parallel computers, all the algorithms are shown to be highly efficient for problems of moderate size. The algorithms using the row-blocked data distribution are the most efficient. 0 1996 by John Wiley & Sons, Inc. chines the potential to solve Grand Challenge-class problems in computational chemistry. In this and a companion article, we report our initial efforts to develop effective ab initio electronic structure codes for MPP computers that are capable of solving problems with 0(102-3) atoms and 0(103-4) basis functions. Problems of this scale almost automatically imply that all matrices be distributed over
Parallel Computing, 2000
In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector±parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. Ó
Parallel calculations of molecular properties
Computer Physics Communications, 2000
We discuss aspects of the parallelization of the Dalton quantum chemistry program, with particular emphasis on the calculation of second-and higher-order properties for large molecules. Our treatment includes real and imaginary perturbations, both frequency-dependent and static. The scaling behaviour of our approach, which is rather coarse-grained, is examined on different parallel platforms, including the Cray-T3E and an IBM SP with the latest multiprocessor nodes. The excellent scaling behaviour on the latter is especially significant given that the first TFLOPS computer available to the US academic community will be built from these nodes and deployed here at San Diego Supercomputer Center before the end of 1999. We then discuss applications of the code to several areas of interest in chemical physics.
Computational Chemistry: The Impact of Massively Parallel Systems
The use of massively parallel computers has allowed us to carry out computational chemistry studies of gas phase and condensed phase systems. Smaller systems can be studied to a more accurate level and in greater detail than previously possible. Thus, the effect of atmospheric water crystals, on reactions aiding ozone depletion over the Antarctic, has been modelled. In addition systems that could not be studied previously are now open to investigation. We have carried out a large number of accurate calculations on the solvation of the Fluoride ion by four water molecules to obtain its thermodynamic characteristics. A project involving the controlled oxidation of hydrocarbons at relatively low temperatures involved the use of serial and parallel machines.
Program package MP-AM1 for parallel quantum-chemical computing in the sp-basis
A parallel realization of the NDDO-WF technique for semi-empirical quantum-chemical calculations on large molecular systems in the spd-basis is described. The technological aspects of designing scalable parallel calculations on super computers (by using MPI library) are discussed. The scaling of individual algorithms and entire package was carried out for two model systems with a number of atomic orbitals of 894 and 2014, respectively. The speedup was determined in computer experiments with the RM600 E60 and Cluster Intel PIII multi-processor systems. The effect of communication rate on the package performance is discussed.
Computational chemistry on Fujitsu vector–parallel processors: Hardware and programming environment
Parallel Computing, 2000
In this and the following paper, we provide an introduction to the Fujitsu VPP range of vector±parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the hardware and the design of software to exploit its capabilities. The VPP employs proprietary vector processors connected via a crossbar switch in a distributed-memory architecture. High single-node performance requires consideration of vector operand lengths, arithmetic pipe utilisation and memory-to-CPU bandwidth. Most parallel chemistry applications use either explicit`message-passing' or a Ôglobal-memoryÕ paradigm, and benchmark results are presented for the communications performance of MPI, Linda and the Global Arrays. Ó
Algorithms vs. architectures for computational chemistry
1990
The algorithms employed are computationally intensive and, as a result, increased performance (both algorithmic and architectural) is required to improve accuracy and to treat larger molecular systems. Several benchmark quantum chemistry codes are examined on a variety of architectures. While these codes are only a small portion of a typical quantum chemistry library, they illustrate many of the computationally intensive kernels and data manipulation requirements of some applications. Furthermore, understanding the performance of the existing algorithm on present and proposed supercomputers serves as a guide for future programs and algorithm development. The algorithms investigated are: (1) a sparse symmetric matrix vector product; (2) a four index integral transformation; and (3) the calculation of diatomic two electron Slater integrals. The vectorization strategies are examined for these algorithms for both the Cyber 205 and Cray XMP. In addition, multiprocessor implementations of...