CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
research
Using lambda networks to enhance performance of interactive large simulations
Authors
P V Coveney
M J Harvey
S Jha
M A Thyveetil
Publication date
1 January 2006
Publisher
'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Cite
Abstract
The ability to use a visualisation tool to steer large simulations provides innovative and novel usage scenarios, e.g. the ability to use new algorithms for the computation of free energy profiles along a nanopore [1]. However, we find that the performance of interactive simulations is sensitive to the quality of service of the network with variable latency and packet loss in particular having a detrimental effect The use of dedicated networks (provisioned in this case as a circuit-switched point-to-point optical lightpath or lambda) can lead to significant (50% or more) performance enhancement, When funning on say 128 or 256 processors of a high-end supercomputer this saving has a significant value. We perform experiments to understand the impact of network characteristics on the performance of a large parallel classical molecular dynamics simulation when coupled interactively to a remote visualisation tool. This paper discusses the experiments performed and presents the results from the systematic studies. © 2006 IEEE.Published versio
Similar works
Full text
Available Versions
Supporting member
Spiral - Imperial College Digital Repository
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:spiral.imperial.ac.uk:1004...
Last time updated on 19/02/2012
Crossref
See this paper in CORE
Go to the repository landing page
Download from data provider
Last time updated on 17/03/2019