2,890 research outputs found
Status and Future Perspectives for Lattice Gauge Theory Calculations to the Exascale and Beyond
In this and a set of companion whitepapers, the USQCD Collaboration lays out
a program of science and computing for lattice gauge theory. These whitepapers
describe how calculation using lattice QCD (and other gauge theories) can aid
the interpretation of ongoing and upcoming experiments in particle and nuclear
physics, as well as inspire new ones.Comment: 44 pages. 1 of USQCD whitepapers
Full QCD on APE100 Machines
We present the first tests and results from a study of QCD with two flavours
of dynamical Wilson fermions using the Hybrid Monte Carlo Algorithm (HMCA) on
APE100 machines.Comment: 23 pages, LaTeX, 13 PS figures not include
Can we do better than Hybrid Monte Carlo in Lattice QCD?
The Hybrid Monte Carlo algorithm for the simulation of QCD with dynamical
staggered fermions is compared with Kramers equation algorithm. We find
substantially different autocorrelation times for local and nonlocal
observables. The calculations have been performed on the parallel computer CRAY
T3D.Comment: Talk presented at LATTICE96(algorithms), LaTeX 3 pages, uses espcrc2,
epsf, 2 postscript figure
Computational Physics on Graphics Processing Units
The use of graphics processing units for scientific computations is an
emerging strategy that can significantly speed up various different algorithms.
In this review, we discuss advances made in the field of computational physics,
focusing on classical molecular dynamics, and on quantum simulations for
electronic structure calculations using the density functional theory, wave
function techniques, and quantum field theory.Comment: Proceedings of the 11th International Conference, PARA 2012,
Helsinki, Finland, June 10-13, 201
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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