Collaborative Environments and Scientific Visualization in Grid

hpdc, 2001

Computational grids are enabling collaboration between scientists and organizations to generate and archive extremely large datasets across shared, distributed resources. There is a need to visually explore such data throughout the life-cycle of projects. Practical exploration of large datasets requires visualization tools that can function in the same grid environment in which the data is created and stored. Resource management interfaces are an important structural component of grid computing environments because they enable uniform access to the wide variety of resources necessary f o r scient@ work. We describe a new advancereservation system f o r graphics resources; and an application of existing grid technology to create general-purpose active storage systems. We report our experience with prototype infrastructure and application components, involving experiments coupling end-to-end resources f o r interactive visual exploration of large data in representative distributed environments.

Distributed Frameworks for Multimedia Applications, 2005

This paper presents an extension of the single-user scientific visualization system ZoomIn to a collaborative system. We discuss the principal challenges of remote collaboration in the case of scientific visualization and present the solutions realized for ZoomIn. The main issues identified include the support of slow/fast network connections, portability, ease-of-use, privacy, configuration of the working mode and permissions. We describe

Proceedings of the 8th …, 2007

Today's large-scale scientific research often relies on the collaborative use of a Grid or e-Science infrastructure (e.g. DEISA, EGEE, TeraGrid, OSG) with computational, storage, or other types of physical resources. One of the goals of these emerging infrastructures is to support the work of scientists with advanced problem-solving tools. Many e-Science applications within these infrastructures aim at simulations of a scientific problem on powerful parallel computing resources. Typically, a researcher first performs a simulation for some fixed amount of time and then analyses results in a separate post-processing step, for instance, by viewing results in visualizations. In earlier work we have described early prototypes of a Collaborative Online Visualization and Steering (COVS) Framework in Grids that performs both -simulation and visualization -at the same time (online) to increase the efficiency of e-Scientists. This paper evaluates the evolved mature reference implementation of the COVS framework design that is ready for production usage within Web service-based Grid and e-Science infrastructures.

Online Proc. of German …, 2007

Many production e-Science infrastructures (e.g. DEISA, D-Grid) have begun to offer a wide variety of services for end-users during the past several years. Many e-Scientists solve their scientific problems by using parallel computing applications on clusters and collaborative online visualization and steering (COVS) is known as a tool for analyzing and better understanding of these applications. In absence of a widely accepted COVS framework within Grids, visualizations are often created using proprietary technologies assuming a dedicated scenario. This makes it feasible to analyze the usual requirements to provide a blueprint for a more general COVS framework that can be integrated into Grid middleware systems such as UNICORE, gLite, or Globus Toolkits. These requirements lead to a design that was successfully implemented as a higher-level service in UNICORE and presented at

Proceedings of the ACM/IEEE SC2004 Conference, 2004

This paper presents a distributed, collaborative grid enabled visualization environment that supports automated resource discovery across heterogeneous machines. Our Resource-Aware Visualization Environment (RAVE) runs as a background process using Grid/Web services, enabling us to share resources with other users rather than commandeering an entire machine. RAVE supports a wide range of machines, from hand-held PDAs to high-end servers with large-scale stereo, tracked displays. The local display device may render all, some or none of the data set remotely, depending on its available resources. This enables scientists and engineers to collaborate from their desks, in the field or in front of specialised immersive displays. We present initial results of our implementation, showing how we distribute complete datasets across multiple machines as required, using a central data service to distribute data updates from collaborating users. We will demonstrate RAVE at SC2004, utilising available heterogeneous resources.

2002

Grid computing infrastructures denote interconnections of massively parallel and distributed computing resources for ubiquitous, integrated, and collaborative usage. While the majority of existing grid software constitutes high-performance and high-throughput batch processing, more and more applications require interactivity and visualization. The latter is supported through the Grid Visualization Kernel (GVK), a middleware extension for fast and efficient interconnection of distant simulation servers and visualization clients. The integration of GVK is provided by specific interface modules for commonly available visualization toolkits, while the actual interconnection is transparently established between arbitrary points on the grid.

Handbook of research on …, 2009

This chapter introduces some aspects of visualization and the grid. Visualization-the art and science of representing data visually-is now recognized as an equal partner in the conduct of science via the simulation and modeling paradigm. Although not usually associated with Grid-scale problems, there are a number of Grid-dominant issues which subtend visualization. Evidently, certain data grooming issues (e.g., image preprocessing/analysis, certain computational geometric processes, certain computational topological processes) are amenable to deployment over compute Grids, but there has been equal focus on the collaborative aspect of Grid computing which is driving collaboration-based visualization systems. Here we survey some of the roles of visualization as they relate to the role of Grid computing within a biomedical context. We conclude by examining certain scheduling strategies we believe to have value in terms of the distribution of visualization tasks over Grid fabrics.

Future Generation Computer Systems, 2003

In a time when computational and data resources are distributed around the globe, users need to interact with these resources and each other easily and efficient. The Grid, by definition, represents a connection of distributed resources that can be used regardless of the user's location. We have built a prototype visualization system using the Globus Toolkit, MPICH-G2, and the Access Grid in order to explore how future scientific collaborations may occur over the Grid. We describe our experience in demonstrating our system at iGrid2002, where the United States and the Netherlands were connected via a high-latency, high-bandwidth network. In particular, we focus on issues related to a Grid-based application that couples a collaboration component (including a user interface to the Access Grid) with a high-resolution remote rendering component. Published by Elsevier Science B.V.

2004

The National Fusion Collaboratory focuses on enabling fusion scientists to explore Grid capabilities in support of experimental science. Fusion experiments are structured as a series of plasma pulses initiated roughly every 20 minutes. In the between-pulse intervals scientists perform data analysis and discuss results to reach decisions affecting changes to the next plasma pulse. This interaction can be made more efficient by performing more analysis and engaging more expertise from a geographically distributed team of scientists and resources. In this paper, we will describe the virtual control room experiment which unites collaborative, visualization and Grid technologies to provide such environment and shows how their combined effect can advance experimental science. We will also report on FusionGrid services whose use during the fusion experimental cycle became possible for the first time thanks to this technology. In terms of technology, we will describe the Access Grid, experimental data presentation tools and agreement-based resource management and workflow systems enabling time-bounded end-to-end application execution. The first virtual control room experiment represented a mock-up of a remote interaction with the DIII-D control room and was presented at SC03 and later reviewed at an international ITER Grid Workshop.

Advanced Engineering Informatics, 2010

This paper discusses the key collaborative features of scientific visualization systems. An experiment with several groups of users has been conducted to evaluate the usability and effectiveness of collaborative tools in such a system. In particular, we compared audio and textual communication support for information exchange as well as the use of graphical indicators. Our analysis revealed the importance of the choice of the conversation means and, surprisingly, the little influence of indicators. Furthermore, the experiments have demonstrated that the system's usability can be significantly improved through appropriate grounding and awareness support. User satisfaction therefore increases, which in turn can potentially also increase the quality of the collaborative work.