The southernmost San Andreas fault has a high probability of rupturing in a large (greater than magnitude 7.5) earthquake sometime during the next few decades. New simulations show that the chain of sedimentary basins between San Bernardino and downtown Los Angeles form an effective waveguide that channels Love waves along the southern edge of the San Bernardino and San Gabriel Mountains. Earthquake scenarios with northward rupture, in which the guided wave is efficiently excited, produce unusually high long‐period ground motions over much of the greater Los Angeles region, including intense, localized amplitude modulations arising from variations in waveguide cross‐section.

While conventional workflow systems have been around for many years, the deployment of analogous systems onto a grid infrastructure introduces a number of unique questions and challenges. Innovative approaches to grid workflow (gridflow) are needed to leverage the heterogeneity, autonomy, dynamic behavior, and wide-area distribution that characterize grid resources. The Matrix Project carries out research and development to deliver the language descriptions and protocols necessary to build collaborative gridflow management systems for the emerging grid infrastructures. We describe here our activities to date including development of the Data Grid Language (DGL) and the usage of the Matrix gridflow management system by the Southern California Earthquake Center (SCEC) to manage its gridflows.

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.

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.

Ensembles of distributed, heterogeneous resources, also known as computational grids, have emerged as critical platforms for high-performance and resource-intensive applications. Such platforms provide the potential for applications to aggregate enormous bandwidth, computational power, memory, secondary storage, and other resources during a single execution. However, achieving this performance potential in dynamic, heterogeneous environments is challenging. Recent experience with distributed applications indicates that adaptivity is fundamental to achieving application performance in dynamic grid environments. The AppLeS (Application Level Scheduling) project provides a methodology, application software, and software environments for adaptively scheduling and deploying applications in heterogeneous, multiuser grid environments. We discuss the AppLeS project and outline our findings.