The emerging cyberinfrastructure holds the promise of providing on-demand access to high performance network, compute and data resources. Image guided neurosurgery is one of many applications that requires such on-demand access to resources. In this paper we have studied the feasibility of accessing such resources on-demand. An experiment was designed and carried out across five TeraGrid clusters for this study. This paper provides an analysis of the results and draws some conclusion regarding feasibility of on-demand access to high performance resources.

The goal of the Encyclopedia of Life (EOL) Project is to predict structural information for all proteins, in all organisms. This calculation presents challenges both in terms of the scale of the computational resources required (approximately 1.8 million CPU hours), as well as in data and workflow management. While tools are available that solve some subsets of these problems, it was necessary for us to build software to integrate and manage the overall Grid application execution. In this paper, we present this workflow system, detail its components, and report on the performance of our initial prototype implementation for runs over a large-scale Grid platform during the SC’03 conference.

Grid workflows can be seen as special scientific workflows involving high performance and/or high throughput computational tasks. Much work in grid workflows has focused on improving application performance through schedulers that optimize the use of computational resources and bandwidth. As high-end computing resources are becoming more of a commodity that is available to new scientific communities, there is an increasing need to also improve the design and reusability “performance” of scientific workflow systems. To this end, we are developing a framework that supports the design and reuse of grid workflows. Individual workflow components (e.g., for data movement, database querying, job scheduling, remote execution etc.) are abstracted into a set of generic, reusable tasks. Instantiations of these common tasks can be functionally equivalent atomic components (called actors) or composite components (so-called composite actors or subworkflows). In this way, a grid workflow designer does not have to commit to a particular Grid technology when developing a scientific workflow; instead different technologies (e.g. GridFTP, SRB, and scp) can be used interchangeably and in concert. We illustrate the application of our framework using two real-world Grid workflows from different scientific domains, i.e., cheminformatics and bioinformatics, respectively.

This chapter contains sections titled: Introduction GAMESS Execution on Clusters Portal Technology Running GAMESS with Nimrod Grid-Enabling Infrastructure Computational Chemistry Workflow Environments Conclusions References

In the future, advanced biomechanical simulations of brain deformation during surgery will require access to multi-teraflop parallel hardware, supporting operating room infrastructure. This will allow surgeons to view images of intra-operative brain deformation within the strict time constraints of the surgical procedure – typically on the order of minutes, multiple times during a six or eight hour long surgery. In this paper we explore the grid infrastructure issues involved in scheduling, on-demand computing, data transfer and parallel finite element biomechanical simulation, which would guarantee that such a dynamic data driven real time application is actually feasible.

Evolving technologies, as exemplified by computational grids and Web services, have made it possible to solve new scientific problems that would not have been feasible previously. In order to make such advances available to the community in general and to be able to solve new problems, not necessarily from the same discipline, it is imperative to build tools that provide a common user interface in order that application programmers and users do not have to be concerned with particulars of Web services and their underlying code, computational platforms, or with data file formats. We will describe our efforts in creating a computational chemistry environment that encompasses a general scientific workflow environment, a domain specific example for quantum chemistry, our ongoing design of a workflow user interface, and our efforts at database integration.

Ensembles of widely distributed, heterogeneous resources, or Grids, have emerged as popular platforms for largescale scientific applications. In this paper we present the Virtual Instrument project, which provides an integrated application execution environment that enables end-users to run and interact with running scientific simulations on Grids. This work is performed in the specific context of MCell, a computational biology application. While MCell provides the basis for running simulations, its capabilities are currently limited in terms of scale, ease-of-use, and interactivity. These limitations preclude usage scenarios that are critical for scientific advances. Our goal is to create a scientific “Virtual Instrument” from MCell by allowing its users to transparently access Grid resources while being able to steer running simulations. In this paper, we motivate the Virtual Instrument project and discuss a number of relevant issues and accomplishments in the area of Grid software development and application scheduling. We then describe our software design and report on the current implementation. We verify and evaluate our design via experiments with MCell on a real-world Grid testbed.

The ongoing global effort of genome sequencing is making large scale comparative proteomic analysis an intriguing task. The Encyclopedia of Life (EOL; http://eol.sdsc.edu) project aims to provide current functional and structural annotations for all available proteomes, a computational challenge never seen before in biology. Using an integrative genome annotation pipeline (iGAP), we have produced 3D models and functional annotations for more than 100 proteomes thus far. This process is greatly facilitated by grid compute resources, and especially by the development of grid application execution environment. AppLeS (Application-Level Scheduling) Parameter Sweep Template (APST) has been adopted by the EOL project as a mediator to grid middleware. APST has made the annotation process much more efficient, highly automated and scalable. Currently we are building a domain-specific bioinformatics workflow management system (BWMS) on top of APST, which further streamlines grid deployment of life science applications. With these developments in mind, we discuss some common problems and expectations of grid computing for high throughput proteomics.

Computational Grids lend themselves well to parameter sweep applications, in which independent tasks calculate results for points in a parameter space. However, it is possible for a parameter space to become so large as to pose prohibitive system requirements. In these cases, user-guided searchespromise to reduce overall computation time. In this paper, we address an interesting challenge posed by these user-directed searches: how should computing resources be allocated to application tasks as the overall computation is being guided by the user? We present a model for user-guided searches, and then propose a number of resource allocation strategies and evaluate them in simulation. We find that prioritizing the assignments of tasks to computing resources throughout the search can lead to substantial performance improvements.

Computational Grids lend themselves well to parameter sweep applications, in which independent tasks calculate results for points in a parameter space. It is possible for a parameter space to become so large as to pose prohibitive system requirements. In these cases, user-directed steering promises to reduce overall computation time. In this paper, we address an interesting challenge posed by these user-directed searches: how should compute resources be allocated to application tasks as the overall computation is being steered by the user? We present a model for user-directed searches, and then propose a number of resource allocation strategies and evaluate them in simulation. We find that prioritizing the assignments of tasks to compute resources throughout the search can lead to substantial performance improvements.

This paper presents the Virtual Instrument project which targets those platforms.More specifically, the project seeks to provide an integrated application execution environment that enables end-usersto run and interact with running scientific simulations on the Grid. This work is performed in the specific contextof a computational biology application: MCell. Even though MCell provides the basis for running simulations, itscapabilities are currently limited in terms of scale, ease-of-use,...