Narrow Results

Two important tools of today's science and engineering are computational grids and visualization. While grid infrastructures offer a means to process large amounts of data across different, possibly distant resources, visualization aids in understanding the meaning of data. The Grid Visualization Kernel (GVK) addresses the connection of grid applications and visualization clients on the grid. The visualization capabilities of GVK are provided as flexible grid services via dedicated interfaces and protocols, while GVK itself relies on Globus services to implement the functionality of the visualization pipeline. This paper describes the concept of GVK and its core functionality for grid visualization services, and discusses how to use visualization in the grid environment.

A computational and data grid was developed at the Center for Computational Research in Buffalo, New York, in order to provide a platform to support scientific and engineering applications across a variety of computer and storage systems. This proof-of-concept grid has been deployed using a critical scientific application in the field of structural biology. The design and functionality of the prototype grid is described, along with plans for a production level grid system based on Globus.

Several aspects of today's Grids are based on centralized or hierarchical services. However, as Grids increase their size from tens to thousands of hosts, functionalities should be decentralized to avoid bottlenecks and guarantee scalability. A way to ensure Grid scalability is to adopt Peer-to-Peer (P2P) models and techniques to implement non-hierarchical decentralized Grid services and systems. Pure decentralized P2P protocols based on a pervasive exchange of messages, such as Gnutella, appear to be inadequate for OGSA Grids, where peers communicate among them through Grid Services mechanisms. On the other hand, this class of protocols offers useful properties in dealing with Grid resources heterogeneity and dynamicity. This paper proposes a modified Gnutella discovery protocol, named Gridnut, which makes it suitable for OGSA Grids. In particular, Gridnut uses appropriate message buffering and merging techniques to make Grid Services effective as a way to exchange messages in a P2P fashion. We present the design of Gridnut and compare Gnutella and Gridnut performances under different network and load conditions.

We present Quantify, a programming framework for exposing high-performance parallel MPI applications using Grid Services. The two distinctive programming styles of Grid Services and MPI are bridged using a data-centric virtualization approach through the notion of Uses and Provides Quantities. Quantities are used to describe an abstract application interface, permit data exchange between applications and facilitate the composition of two or more applications in a service workflow. Uses and Provides Quantities are modelled using Service Data Elements (SDEs). Finally we demonstrate the applicability of the framework using a Flood Crisis application scenario.