Computational Grids lend themselves well to parameter sweep applications,which consist of independent tasks, each of which calculates results for a separate point in parameter space. However, 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. We present experimental results obtained with software developed as part of the Virtual Instrument project, and discuss the impact of our findings on future Virtual Instrument implementations.

Pre-2018 CSE ID: CS2002-0720

Ensembles of distributed, heterogeneous resources, or Computational Grids, have emerged as popular platforms for large-scale scientific applications. 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-users to run and interact with running scientific simulations on the Grid. This work is performed in the specific context of a computational biology application: MCell. Even though MCell provides the basis for running simulations, its capabilities are currently limited in terms of scale, ease-of-use, and interactivity. Those 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 need for an MCell Virtual Instrument. We then introduce a scheduling strategy that exploits the structure of MCell simulations and uses task priorities to accommodates computational steering. Finally, we describe our innovations and contributions in terms of Grid software design and development.

Pre-2018 CSE ID: CS2002-0707