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.
Disciplines
Chemistry | Computer Sciences
CommentsThe following article appeared Abstract: 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.
We continue the study of a particle (atom, molecule) undergoing an unbiased random walk on the Sierpinski gasket, and obtain for the gasket and tower the eigenvalue spectrum of the associated stochastic master equation. Analytic expressions for recurrence relations among the eigenvalues are derived. The recurrence relations obtained are compared with those determined for two Euclidean lattices, the closed chain with an absorbing site and a finite chain with an absorbing site at one end. We check and confirm the internal consistency between the smallest eigenvalue and the mean walklength in each of the cases studied. Attention is drawn to the relevance of the results obtained to a problem of electron transfer in proteins.
An analytical method based on the classical ruin problem is developed to
compute the mean reaction time between two walkers undergoing a generalized
random walk on a 1d lattice. At each time step, either both walkers diffuse
simultaneously with probability $p$ (synchronous event) or one of them diffuses
while the other remains immobile with complementary probability (asynchronous
event). Reaction takes place through same site occupation or position exchange.
We study the influence of the degree of synchronicity $p$ of the walkers and
the lattice size $N$ on the global reaction's efficiency. For odd $N$, the
purely synchronous case ($p=1$) is always the most effective one, while for
even $N$, the encounter time is minimized by a combination of synchronous and
asynchronous events. This new parity effect is fully confirmed by Monte Carlo
simulations on 1d lattices as well as for 2d and 3d lattices. In contrast, the
1d continuum approximation valid for sufficiently large lattices predicts a
monotonic increase of the efficiency as a function of $p$. The relevance of the
model for several research areas is briefly discussed.Comment: 21 pages (including 12 figures and 4 tables), uses revtex4.cls,
accepted for publication in Physica
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