This paper motivates how collaborative tools are needed to support modern computational science, using the case study of a distributed team of numerical relativists developing and running codes to model black holes and other astrophysical objects. We describe a summary of previous tools developed within the collaboration, and how they are integrated and used with their simulation codes which are built using the Cactus framework. We also describe new Cactus tools which use the Twitter and Flickr services. These tools are fundamentally integrated with the code base as Cactus modules and provide reliable, real-time information about simulations that can be easily shared across a collaboration.

In Grid computing multiple, incompatible middleware frameworks exist and are widely used in large research and production environments. Standard specifications for such Grid middleware are rarely available, and often still unstable. This hinders the ability of application programmers to write portable Grid application code.The Simple API for Grid Applications (SAGA) is an ongoing standardization effort within the Open Grid Forum (OGF). The SAGA API provides a simple, uniform interface for applications which utilize very dynamic and heterogeneous Grid environments. With SAGA, programmers of high-level Grid application do not have to learn about underlying Grid middleware layers and frameworks.Our newly developed SAGA C++ reference implementation makes this API available for real-world applications, providing a flexible, extensible, portable, and generic framework usable in dynamic environments.This poster describes the key features of SAGA, and provides examples of its use from the C++ reference implementation.

Einstein's equations of general relativity govern such exotic phenomena as black holes, neutron stars, and gravitational waves. Known for nearly a century, they are among the most complex in physics, and require very large scale computational power - which we are just on the verge of achieving - and advanced algorithms, to solve in the general case. I will motivate and describe the structure of these equations, and the worldwide effort to develop advanced and collaborative computational tools utilizing supercomputers, data archives, optical networks, grids, and advanced software to solve them in their full generality. I will focus on applications of these tools to extract new physics of relativistic astrophysical systems. In particular, I will summarize recent progress in the study of black hole collisions, considered to be promising sources of observable gravitational waves that may soon be seen for the first time by the worldwide network of gravitational wave detectors (LIGO, VIRGO, GEO, and others).

Core Grid technologies are rapidly maturing, but there remains a shortage of real Grid applications. One important reason is the lack of a simple and high-level application programming toolkit, bridging the gap between existing Grid middleware and application-level needs. The Grid Application Toolkit (GAT), as currently developed by the EC-funded project GridLab, provides this missing functionality. As seen from the application, the GAT provides a unified simple programming interface to the Grid infrastructure, tailored to the needs of Grid application programmers and users. A uniform programming interface will be needed for application developers to create a new generation of "Grid-aware" applications. The GAT implementation handles both the complexity and the variety of existing Grid middleware services via so-called adaptors. Complementing existing Grid middleware, GridLab also provides high-level services to implement the GAT functionality. We present the GridLab software architecture, consisting of the GAT, environment-specific adaptors, and GridLab services. We elaborate the concepts underlying the GAT and outline the corresponding application programming interface. We present the functionality of GridLab's high-level services and demonstrate how a dynamic Grid application can easily benefit from the GAT. All GridLab software is open source and can be downloaded from the project Web site.

Nomadic Migration describes a technology, which provides an application with the ability to seek out and exploit remote computing resources by migrating tasks from site to site, dynamically adapting the application to a changing Grid environment. By automating the detection and usage of free resources in a global Grid, we achieve a significantly faster throughput than by manually interfacing with these resources. In this Paper we discuss the Peer-To-Peer strategy as an approach to provide a fault tolerant service infrastructure, required for a stable Grid Migration Service in an intrinsically disruptive Grid environment. The migration technology presented here is e.g. used with large-scale, Cactus based HPC simulations.

We present a synopsis of the Grid Application Toolkit, under development in the EU GridLab project, along with some of the new application scenarios which it will enable.

Abstract We describe a Grid‐based collaboratory that supports the collaborative development and use of advanced simulation codes. Our implementation of this collaboratory uses a mix of Web technologies (for thin‐client access) and Grid services (for secure remote access to, and management of, distributed resources). Our collaboratory enables researchers in geographically disperse locations to share and access compute, storage, and code resources, without regard to institutional boundaries. Specialized services support community code development, via specialized Grid services, such as online code repositories. We use this framework to construct the Astrophysics Simulation Collaboratory, a domain‐specific collaboratory for the astrophysics simulation community. This Grid‐based collaboratory enables researchers in the field of numerical relativity to study astrophysical phenomena by using the Cactus computational toolkit. Copyright © 2002 John Wiley & Sons, Ltd.

The Testbed and Applications working group of the European Grid Forum (EGrid) is actively building and experimenting with a grid infrastructure connecting several research-based supercomputing sites located in Europe. The paper reports on our first feasibility study: running a self-migrating version of the Cactus simulation code across the European grid testbed, including "live" remote data visualization and steering from different demonstration booths at Supercomputing 2000, in Dallas, TX. We report on the problems that had to be resolved for this endeavour and identify open research challenges for building production-grade grid environments.

We discuss a set of novel techniques we are developing, which build on standard tools, to make distributed computing for large-scale simulations across multiple machines (even scattered across different continents) a reality. With these techniques we demonstrate that we are able to scale a tightly coupled scientific application in metacomputing environments. Such research and development in metacomputing will lead the way to routine, straightforward and efficient use of distributed computing resources anywhere around the world. This work applies not only to the large-scale simulations in astrophysics which provide the motivation for this work, but also opens the way for new, innovative application scenarios.

We describe the design and implementation of a technology which provides an application with the ability to seek out and exploit remote computing resources by migrating tasks from site to site, dynamically adapting the application to a changing Grid environment. The motivation for this migration framework, dubbed "The Worm", originated from the experience of having an abundance of computing time for simulations, which is distributed over multiple sites and split in time chunks by queuing systems. We describe the architecture of the Worm, describing how new or more suitable resources are located, and how the payload simulation is migrated to these resources following a trigger event. The migration technology presented here is designed to be used for any application, including large-scale HPC simulations.

Grid Portals, based on standard Web technologies, are emerging as important and useful user interfaces to computational and data grids. Grid portals enable virtual organizations, comprised of distributed researchers to collaborate and access resources more efficiently and seamlessly. The Astrophysics Simulation Collaboratory (ASC) Grid Portal provides a framework to enable researchers in the field of numerical relativity to study astrophysical phenomenon by making use of the Cactus computational toolkit. We examine user requirements and describe the design and implementation of the ASC Grid Portal.

Improvements in the performance of processors and networks make it both feasible and interesting to treat collections of workstations, servers, clusters, and supercomputers as integrated computational resources, or Grids. However, the highly heterogeneous and dynamic nature of such Grids can make application development difficult. Here we describe an architecture and prototype implementation for a Grid-enabled computational framework based on Cactus, the MPICH-G2 Grid-enabled message-passing library, and a variety of specialized features to support efficient execution in Grid environments. We have used this framework to perform record-setting computations in numerical relativity, running across four supercomputers and achieving scaling of 88% (1140 CPU's) and 63% (1500 CPUs). The problem size we were able to compute was about five times larger than any other previous run. Further, we introduce and demonstrate adaptive methods that automatically adjust computational parameters during run time, to increase dramatically the efficiency of a distributed Grid simulation, without modification of the application and without any knowledge of the underlying network connecting the distributed computers.

Cactus is an open source problem solving environment designed for scientists and engineers. Its modular structure facilitates parallel computation across different architectures and collaborative code development between different groups. The Cactus Code originated in the academic research community, where it has been developed and used over many years by a large international collaboration of physicists and computational scientists. We discuss how the intensive computing requirements of physics applications now using the Cactus Code encourage the use of distributed and metacomputing, describe the development and experiments which have already been performed with Cactus, and detail how its design makes it an ideal application test-bed for Grid computing.

We are developing a system for collaborative research and development for a distributed group of researchers at different institutions around the world. In a new paradigm for collaborative computational science, the computer code and supporting infrastructure itself becomes the collaborating instrument, just as an accelerator becomes the collaborating tool for large numbers of distributed researchers in particle physics. The design of this "collaboratory" allows many users, with very different areas of expertise, to work coherently together, on distributed computers around the world. Different supercomputers may be used separately, or for problems exceeding the capacity of any single system, multiple supercomputers may be networked together through high speed gigabit networks. Central to this collaboratory is a new type of community simulation code, called "Cactus". The scientific driving force behind this project is the simulation of Einstein's equations for studying black holes, gravitational waves, and neutron stars, which has brought together researchers in very different fields from many groups around the world to make advances in the study of relativity and astrophysics. But the system is also being developed to provide scientists and engineers, without expert knowledge of parallel or distributed computing, mesh refinement, and so on, with a simple framework for solving any system of partial differential equations on many parallel computer systems, from traditional supercomputers to networks of workstations.