From interactive applications to distributed laboratories (original) (raw)
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An Environment for Web-based Interaction and Steering of High-Performance Scientific Applications
2000
This paper presents an environment for Web-based interrogation, interaction and steering of high-performance parallel/distributed scientific applications. The architecture is composed of detachable thin-clients at the front-end, a network of Java interaction servers in the middle, and [a control network of sensors, actuators, interaction agents, and an application interaction proxy, superimposed on the application data-network, at the back-end. A key innovation of the architecture is the definition of interaction enabled Java proxies, (using the Java Native Interface), for distributed application computational objects. The interaction objects along with the application interaction proxy provide window into application execution, which can be accessed through the interaction web-server. The presented environment is part of an ongoing effort to develop and deploy a web-based computation collaboratory that enables geographically distributed scientists and engineers to collaboratively monitor, and control distributed applications. Its overall aim is to bring large distributed simulations to the scientist/engineers desktop by providing collaborative web-based portals for interaction and control.
Interactive Computing Framework for Engineering Applications
2015
Abstract: Problem statement: Even though the computational steering state-of-the-art environments allow users to embed their simulation codes as a module for an interactive steering without the necessity for their own expertise in high-performance computing and visualisation, e.g., these environments are limited in their possible applications and mostly entail heavy code changes in order to integrate the existing code. Approach: In this study, we introduce an integration framework for engineering applications that supports distributed computations as well as visualization on-the-fly in order to reduce latency and enable a high degree of interactivity with only minor code alterations involved. Moreover, we tackle the problem of long communication delays in the case of huge data advent, which occur due to rigid coupling of simulation back-ends with visualization front-ends and handicap a user in exploring intuitively the relation of cause and effect. Results: The results for the first...
A High-Performance Interactive Computing Framework for Engineering Applications
Lecture Notes in Computational Science and Engineering, 2013
To harness the potential of advanced computing technologies, efficient (real time) analysis of large amounts of data is as essential as are front-line simulations. In order to optimise this process, experts need to be supported by appropriate tools that allow to interactively guide both the computation and data exploration of the underlying simulation code. The main challenge is to seamlessly feed the user requirements back into the simulation. State-of-the-art attempts to achieve this, have resulted in the insertion of so-called check-and break-points at fixed places in the code. Depending on the size of the problem, this can still compromise the benefits of such an attempt, thus, preventing the experience of real interactive computing. To leverage the concept for a broader scope of applications, it is essential that a user receives an immediate response from the simulation to his or her changes. Our generic integration framework, targeted to the needs of the computational engineering domain, supports distributed computations as well as on-the-fly visualisation in order to reduce latency and enable a high degree of interactivity with only minor code modifications. Namely, the regular course of the simulation coupled to our framework is interrupted in small, cyclic intervals followed by a check for updates. When new data is received, the simulation restarts automatically with the updated settings (boundary conditions, simulation parameters, etc.). To obtain rapid, albeit approximate feedback from the simulation in case of perpetual user interaction, a multi-hierarchical approach is advantageous. Within several different engineering test cases, we will demonstrate the flexibility and the effectiveness of our approach.
Collaborative Interactivity in Parallel HPC Applications
Remote Instrumentation and Virtual Laboratories, 2010
Large-scale scientific research often relies on the collaborative use of massive computational power, fast networks, and large storage capacities provided by e-science infrastructures (e.g. deisa, egee, etc.) since the past several years. Especially within e-science infrastructures driven by high-performance computing (hpc) such as deisa, collaborative online visualization and computational steering (covs) has become an important technique to enable hpc applications with interactivity and visualized feedback mechanisms. In earlier work we have shown a prototype covs technique implementation based on the visualization interface toolkit (visit) and the Grid middleware of deisa named as Uniform Interface to Computing Resources (unicore). Since then the approach grew to a broader covs framework. More recently, we investigated the impact of using the computational steering capabilities of the covs framework implementation in unicore on large-scale hpc systems (i.e. ibm BlueGene/P with 65536 processors) and the use of attribute-based authorization. In this paper we emphasize on the improved collaborative features of the covs framework and present new insights of how we deal with dynamic management of n participants, transparency of Grid resources, and virtualization of hosts of end-users. We also show that our interactive approach to hpc systems fully supports the necessary single sign-on feature required in Grid and e-science infrastructures.
The Laboratory Bench: Distributed Computing for Parametised Simulations
1994
This paper concerns the use of distributed computers for solving large scientific modelling problems. In many fields, a designer may wish to explore a set of alternative scenarios. If numerical simulation is used as the experimental process, then this means executing a number of independent jobs and then aggregating the results in some way. There are currently two main ways of organising the execution on multiple computers, namely the use of remote job execution systems, or building distributed applications. This paper explores both of these, and proposes a user interface based on a laboratory bench metaphor. It then describes a prototype system with the advantages of both current job generation methods. The system is built on top of the Distributed Computing Environment from the Open Software Foundation. A real world example, photo chemical pollution modelling, is used as a sample application.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2005
The grid has the potential to transform collaborative scientific investigations through the use of closely coupled computational and visualization resources, which may be geographically distributed, in order to harness greater power than is available at a single site. Scientific applications to benefit from the grid include visualization, computational science, environmental modelling and medical imaging. Unfortunately, the diversity, scale and location of the required resources can present a dilemma for the scientific worker because of the complexity of the underlying technology. As the scale of the scientific problem under investigation increases so does the nature of the scientist's interaction with the supporting infrastructure. The increased distribution of people and resources within a grid-based environment can make resource sharing and collaborative interaction a critical factor to their success. Unless the technological barriers affecting user accessibility are reduced,...
Web based collaborative visualization of distributed and parallel simulation
Proceedings 1999 IEEE Parallel Visualization and Graphics Symposium (Cat. No.99EX381), 1999
This paper presents an interaction model to support collaborative scienti c visualization. Relevant prior work is presented to contextualize the model and its import. An implementation of the model is presented within a collaborative system that supports exible collaborative coupling of multiuser applications. Two example applications are presented to demonstrate the capabilities of the model. The implementation is Web based, fully supports multiuser interfaces, uses VRML for three dimensional graphic display, and is implemented in Java with CORBA support for external server access.
6A. 8 Tools for Integrating Distributed Computing with Interactive Visualization in McIdas-V
ams.confex.com
We present an overview and demonstration of open-source tools and technologies used to make large-scale computing connect readily to client visualization environments, bringing together multiple data sources to compose analyses in the McIDAS-V environment. McIDAS-V permits novel manipulations of atmospheric datasets distributed across the network using 3-D graphics and a highly literate data model implemented in Java. When coupled with plug-ins permitting it access to web services, cluster and grid computing can be made both easy-to-use and scriptable. Outputs can be sliced, subsetted and integrated into visualizations and further computations. This technology demonstration is intended to evolve into a toolkit and best practices for integrating heritage data processing applications with distributed computing and visualization.
A Grid Infrastructure for Parallel and Interactive Applications
2008
The int.eu.grid project aims at providing a production quality grid computing infrastructure for e-Science supporting parallel and interactive applications. The infrastructure capacity is presently about 750 cpu cores distributed over twelve sites in seven countries. These resources have to be tightly coordinated to match the requirements of parallel computing. Such an infrastructure implies high availability, performance and robustness resulting in a much larger management effort than in traditional grid environments which are usually targeted to run sequential non-interactive applications. To achieve these goals the int.eu.grid project offers advanced brokering mechanisms and user friendly graphical interfaces supporting application steering. The int.eu.grid environment is deployed on top of the J. Gomes et al. gLite middleware enabling full interoperability with existing gLite based infrastructures.