32,573 research outputs found
Accelerating scientific codes by performance and accuracy modeling
Scientific software is often driven by multiple parameters that affect both
accuracy and performance. Since finding the optimal configuration of these
parameters is a highly complex task, it extremely common that the software is
used suboptimally. In a typical scenario, accuracy requirements are imposed,
and attained through suboptimal performance. In this paper, we present a
methodology for the automatic selection of parameters for simulation codes, and
a corresponding prototype tool. To be amenable to our methodology, the target
code must expose the parameters affecting accuracy and performance, and there
must be formulas available for error bounds and computational complexity of the
underlying methods. As a case study, we consider the particle-particle
particle-mesh method (PPPM) from the LAMMPS suite for molecular dynamics, and
use our tool to identify configurations of the input parameters that achieve a
given accuracy in the shortest execution time. When compared with the
configurations suggested by expert users, the parameters selected by our tool
yield reductions in the time-to-solution ranging between 10% and 60%. In other
words, for the typical scenario where a fixed number of core-hours are granted
and simulations of a fixed number of timesteps are to be run, usage of our tool
may allow up to twice as many simulations. While we develop our ideas using
LAMMPS as computational framework and use the PPPM method for dispersion as
case study, the methodology is general and valid for a range of software tools
and methods
Algorithmic differentiation and the calculation of forces by quantum Monte Carlo
We describe an efficient algorithm to compute forces in quantum Monte Carlo
using adjoint algorithmic differentiation. This allows us to apply the space
warp coordinate transformation in differential form, and compute all the 3M
force components of a system with M atoms with a computational effort
comparable with the one to obtain the total energy. Few examples illustrating
the method for an electronic system containing several water molecules are
presented. With the present technique, the calculation of finite-temperature
thermodynamic properties of materials with quantum Monte Carlo will be feasible
in the near future.Comment: 32 pages, 4 figure, to appear in The Journal of Chemical Physic
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
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