4,780 research outputs found
Limits on Fundamental Limits to Computation
An indispensable part of our lives, computing has also become essential to
industries and governments. Steady improvements in computer hardware have been
supported by periodic doubling of transistor densities in integrated circuits
over the last fifty years. Such Moore scaling now requires increasingly heroic
efforts, stimulating research in alternative hardware and stirring controversy.
To help evaluate emerging technologies and enrich our understanding of
integrated-circuit scaling, we review fundamental limits to computation: in
manufacturing, energy, physical space, design and verification effort, and
algorithms. To outline what is achievable in principle and in practice, we
recall how some limits were circumvented, compare loose and tight limits. We
also point out that engineering difficulties encountered by emerging
technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl
Observation of a Modulational Instability in Bose-Einstein condensates
We observe the breakup dynamics of an elongated cloud of condensed Rb
atoms placed in an optical waveguide. The number of localized spatial
components observed in the breakup is compared with the number of solitons
predicted by a plane-wave stability analysis of the nonpolynomial nonlinear
Schr\"odinger equation, an effective one-dimensional approximation of the
Gross-Pitaevskii equation for cigar-shaped condensates. It is shown that the
numbers predicted from the fastest growing sidebands are consistent with the
experimental data, suggesting that modulational instability is the key
underlying physical mechanism driving the breakup.Comment: 6 pages, 5 figure
Chiminey: Reliable Computing and Data Management Platform in the Cloud
The enabling of scientific experiments that are embarrassingly parallel, long
running and data-intensive into a cloud-based execution environment is a
desirable, though complex undertaking for many researchers. The management of
such virtual environments is cumbersome and not necessarily within the core
skill set for scientists and engineers. We present here Chiminey, a software
platform that enables researchers to (i) run applications on both traditional
high-performance computing and cloud-based computing infrastructures, (ii)
handle failure during execution, (iii) curate and visualise execution outputs,
(iv) share such data with collaborators or the public, and (v) search for
publicly available data.Comment: Preprint, ICSE 201
AiiDA: Automated Interactive Infrastructure and Database for Computational Science
Computational science has seen in the last decades a spectacular rise in the
scope, breadth, and depth of its efforts. Notwithstanding this prevalence and
impact, it is often still performed using the renaissance model of individual
artisans gathered in a workshop, under the guidance of an established
practitioner. Great benefits could follow instead from adopting concepts and
tools coming from computer science to manage, preserve, and share these
computational efforts. We illustrate here our paradigm sustaining such vision,
based around the four pillars of Automation, Data, Environment, and Sharing. We
then discuss its implementation in the open-source AiiDA platform
(http://www.aiida.net), that has been tuned first to the demands of
computational materials science. AiiDA's design is based on directed acyclic
graphs to track the provenance of data and calculations, and ensure
preservation and searchability. Remote computational resources are managed
transparently, and automation is coupled with data storage to ensure
reproducibility. Last, complex sequences of calculations can be encoded into
scientific workflows. We believe that AiiDA's design and its sharing
capabilities will encourage the creation of social ecosystems to disseminate
codes, data, and scientific workflows.Comment: 30 pages, 7 figure
Workflow Engineering in Materials Design within the BATTERY 2030+ Project
In recent years, modeling and simulation of materials have become indispensable to complement experiments in materials design. High-throughput simulations increasingly aid researchers in selecting the most promising materials for experimental studies or by providing insights inaccessible by experiment. However, this often requires multiple simulation tools to meet the modeling goal. As a result, methods and tools are needed to enable extensive-scale simulations with streamlined execution of all tasks within a complex simulation protocol, including the transfer and adaptation of data between calculations. These methods should allow rapid prototyping of new protocols and proper documentation of the process. Here an overview of the benefits and challenges of workflow engineering in virtual material design is presented. Furthermore, a selection of prominent scientific workflow frameworks used for the research in the BATTERY 2030+ project is presented. Their strengths and weaknesses as well as a selection of use cases in which workflow frameworks significantly contributed to the respective studies are discussed
QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion Quantum Monte Carlo
We review recent advances in the capabilities of the open source ab initio
Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for
greater efficiency and reproducibility. The auxiliary field QMC (AFQMC)
implementation has been greatly expanded to include k-point symmetries,
tensor-hypercontraction, and accelerated graphical processing unit (GPU)
support. These scaling and memory reductions greatly increase the number of
orbitals that can practically be included in AFQMC calculations, increasing
accuracy. Advances in real space methods include techniques for accurate
computation of band gaps and for systematically improving the nodal surface of
ground state wavefunctions. Results of these calculations can be used to
validate application of more approximate electronic structure methods including
GW and density functional based techniques. To provide an improved foundation
for these calculations we utilize a new set of correlation-consistent effective
core potentials (pseudopotentials) that are more accurate than previous sets;
these can also be applied in quantum-chemical and other many-body applications,
not only QMC. These advances increase the efficiency, accuracy, and range of
properties that can be studied in both molecules and materials with QMC and
QMCPACK
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