Reducing Complexity in Management of eScience
Computations
Abstract: In this paper we address reduction of complexity in management of
scientific computations in distributed computing environments. We explore an
approach based on separation of computation design (application development)
and distributed execution of computations, and investigate best practices for
construction of virtual infrastructures for computational science - software
systems that abstract and virtualize the processes of
managing scientific computations on heterogeneous distributed resource systems.
As a result we present StratUm, a toolkit for
management of eScience computations. To illustrate
use of the toolkit, we present it in the context of a case study where we
extend the capabilities of an existing kinetic Monte Carlo software framework
to utilize distributed computational resources. The case study illustrates a
viable design pattern for construction of virtual infrastructures for
distributed scientific computing. The resulting infrastructure is evaluated
using a computational experiment from molecular systems biology.
Conservative Distributed Discrete Event Simulation on Amazon EC2
Abstract: A discrete-event simulator's ability to distribute the execution of a
simulation model allows one to deal with the memory limitations of a single
computational resource, and thereby increase the scale or level of detail at
which models can be studied. In addition, distribution has the potential to
reduce the round trip time of a simulation by incorporating multiple
computational cores into the simulation's execution. However, such gains can be
voided by the overhead that time synchronization protocols introduce. These
protocols are required to prevent the occurrence of causality errors during a
parallel execution of a simulation. The overhead depends on the protocol,
characteristics of the simulation model, and the architecture of the computational resources used. Recently,
infrastructure-as-a-service offerings in cloud computing have introduced
flexibility in acquiring computational resources on a pay-as-you-go basis. At
present, it is unclear to what extent these offerings are suited for the
distributed execution of discrete-event simulations, and how the
characteristics of different resource types impact the runtime performance of
distributed simulations. In this paper we investigate this issue, and assess
the performance of different conservative time synchronization protocols on a
range of cloud resource types that are currently available on Amazon EC2.
On HLA-based Service Oriented Simulation: an
Integrative Approach
Abstract: The High Level Architecture (HLA) has become the de-facto standard in
simulation and simulation interoperability. This paper discusses HLA and its
possible integration in a Service-Oriented simulation framework. First it
presents the technology roadmap of HLA since its first introduction together
with several implementations in the industry today. The paper then focuses on
the integration of an HLA RTI in the Service-Oriented Framework of the FCINT
smart building project.
Simulation in the Cloud Using Handheld Devices
Abstract: In recent years, numerous applications have been deployed into mobile
devices. However, until now, there have been no attempts to run simulations on
handheld devices. We want investigate different architectures for running and
managing simulations on handheld devices, and putting the simulation services
in the Cloud. We propose a hybrid simulation and visualization approach, where
a dedicated mobile application is running on the client side and the RISE
simulation server is hosted in the Cloud. In particular, with our prototype, we
explore the remote management of a simulation tool using a dedicated native
application running on an Android Smartphone, and showing the evolution of a
simulation model for a forest fire spread, mashing-up the generated graphics
with online GIS services.
Goal-Directed
Grid-Enabled Computing for Legacy Simulations
Abstract: We describe a middleware framework conceived to enhance the
effectiveness and efficiency of existing simulation applications by providing
three capabilities: (1) access to grid-based and cloud-based execution, (2)
access to advanced Design of Experiments (DOE) methodologies such as
simulation-based optimization, and (3) access to robust data processing and
visualization. The framework has been applied to a variety of simulations in
both commercial and open source programming languages employing both discrete
and continuous modeling formalisms. A key design objective is to minimize the
workload necessary to adapt a simulation for use with the framework. User
experience to date reveals that the learning curve for the framework is
reasonable, but further automation of key tasks would enhance the framework's
utility.
U.S. Army Modeling and Simulation Executable
Architecture Deployment Cloud Virtualization Strategy
Abstract: Our research has included leveraging Virtualization Technologies to
provide integration, configuration and execution relief of Modeling &
Simulation (M&S) event planning, instantiation and analysis. We have
achieved this through a single service that is used to deploy and execute stand-alone
applications as well as separate, but cooperative, applications on a dynamic
virtual machine-based cloud. This use of virtualization technology shows
significant cost savings in reducing the human effort for integration, test and
execution by providing a powerful virtual machine environment that combines new
and existing applications and their configurations. Our effort eliminates the
time needed to manually configure and execute these applications on physical
hardware once they are captured in the system.
Simulation Processes In The Cloud for Emergency
Planning
Abstract: In recent years, various environmental disasters (tsunamis, earthquakes,
forest fires and nuclear incidents) have caused numerous losses in lives and
infrastructure. In such emergency, remote access to the simulation resources
can increase the emergency response success. We propose a new architecture
based on the RISE simulation services middleware and on Taverna
workflow to execute the entire simulation process into the Cloud. We present
its use through an emergency flooding scenario use case in which emergency crew
can order a new simulation and visualize result on GoogleEarth.
Development of a metamodel for medical database management on a grid network
Abstract: Centralized management of patient data is no more a viable solution. In many countries, patient identification restrictions due to privacy laws implies developing thorough mechanism to avoid duplicates and information loss. In this paper we present a work in progress dealing with a grid distributed medical data base.GPU based identification algorithms for disease surveillance, medical data exchange and epidemiological analyses..