653 research outputs found
Efficient numerical integrators for stochastic models
The efficient simulation of models defined in terms of stochastic
differential equations (SDEs) depends critically on an efficient integration
scheme. In this article, we investigate under which conditions the integration
schemes for general SDEs can be derived using the Trotter expansion. It follows
that, in the stochastic case, some care is required in splitting the stochastic
generator. We test the Trotter integrators on an energy-conserving Brownian
model and derive a new numerical scheme for dissipative particle dynamics. We
find that the stochastic Trotter scheme provides a mathematically correct and
easy-to-use method which should find wide applicability.Comment: v
A semi-analytical approach to molecular dynamics
Despite numerous computational advances over the last few decades, molecular dynamics still favors explicit (and thus easily-parallelizable) time integrators for large scale numerical simulation. As a consequence, computational efficiency in solving its typically stiff oscillatory equations of motion is hampered by stringent stability requirements on the time step size. In this paper, we present a semi-analytical integration scheme that offers a total speedup of a factor 30 compared to the Verlet method on typical MD simulation by allowing over three orders of magnitude larger step sizes. By efficiently approximating the exact integration of the strong (harmonic) forces of covalent bonds through matrix functions, far improved stability with respect to time step size is achieved without sacrificing the explicit, symplectic, time-reversible, or fine-grained parallelizable nature of the integration scheme. We demonstrate the efficiency and scalability of our integrator on simulations ranging from DNA strand unbinding and protein folding to nanotube resonators
The High-Order Symplectic Finite-Difference Time-Domain Scheme
published_or_final_versio
QCD simulations with staggered fermions on GPUs
We report on our implementation of the RHMC algorithm for the simulation of
lattice QCD with two staggered flavors on Graphics Processing Units, using the
NVIDIA CUDA programming language. The main feature of our code is that the GPU
is not used just as an accelerator, but instead the whole Molecular Dynamics
trajectory is performed on it. After pointing out the main bottlenecks and how
to circumvent them, we discuss the obtained performances. We present some
preliminary results regarding OpenCL and multiGPU extensions of our code and
discuss future perspectives.Comment: 22 pages, 14 eps figures, final version to be published in Computer
Physics Communication
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