4,737 research outputs found
A sweep algorithm for massively parallel simulation of circuit-switched networks
A new massively parallel algorithm is presented for simulating large asymmetric circuit-switched networks, controlled by a randomized-routing policy that includes trunk-reservation. A single instruction multiple data (SIMD) implementation is described, and corresponding experiments on a 16384 processor MasPar parallel computer are reported. A multiple instruction multiple data (MIMD) implementation is also described, and corresponding experiments on an Intel IPSC/860 parallel computer, using 16 processors, are reported. By exploiting parallelism, our algorithm increases the possible execution rate of such complex simulations by as much as an order of magnitude
Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification
A massively parallel method to build large transition rate matrices from
temperature accelerated molecular dynamics trajectories is presented. Bayesian
Markov model analysis is used to estimate the expected residence time in the
known state space, providing crucial uncertainty quantification for higher
scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The
estimators are additionally used to optimize where exploration is performed and
the degree of temperature ac- celeration on the fly, giving an autonomous,
optimal procedure to explore the state space of complex systems. The method is
tested against exactly solvable models and used to explore the dynamics of C15
interstitial defects in iron. Our uncertainty quantification scheme allows for
accurate modeling of the evolution of these defects over timescales of several
seconds.Comment: 14 pages, 7 figure
Parallelization of a Dynamic Monte Carlo Algorithm: a Partially Rejection-Free Conservative Approach
We experiment with a massively parallel implementation of an algorithm for
simulating the dynamics of metastable decay in kinetic Ising models. The
parallel scheme is directly applicable to a wide range of stochastic cellular
automata where the discrete events (updates) are Poisson arrivals. For high
performance, we utilize a continuous-time, asynchronous parallel version of the
n-fold way rejection-free algorithm. Each processing element carries an lxl
block of spins, and we employ the fast SHMEM-library routines on the Cray T3E
distributed-memory parallel architecture. Different processing elements have
different local simulated times. To ensure causality, the algorithm handles the
asynchrony in a conservative fashion. Despite relatively low utilization and an
intricate relationship between the average time increment and the size of the
spin blocks, we find that for sufficiently large l the algorithm outperforms
its corresponding parallel Metropolis (non-rejection-free) counterpart. As an
example application, we present results for metastable decay in a model
ferromagnetic or ferroelectric film, observed with a probe of area smaller than
the total system.Comment: 17 pages, 7 figures, RevTex; submitted to the Journal of
Computational Physic
Simulation of a Hard-Spherocylinder Liquid Crystal with the pe
The pe physics engine is validated through the simulation of a liquid crystal
model system consisting of hard spherocylinders. For this purpose we evaluate
several characteristic parameters of this system, namely the nematic order
parameter, the pressure, and the Frank elastic constants. We compare these to
the values reported in literature and find a very good agreement, which
demonstrates that the pe physics engine can accurately treat such densely
packed particle systems. Simultaneously we are able to examine the influence of
finite size effects, especially on the evaluation of the Frank elastic
constants, as we are far less restricted in system size than earlier
simulations
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