We describe the Einstein Toolkit, a community-driven, freely accessible computational infrastructure intended for use in numerical relativity, relativistic astrophysics, and other applications. The Toolkit, developed by a collaboration involving researchers from multiple institutions around the world, combines a core set of components needed to simulate astrophysical objects such as black holes, compact objects, and collapsing stars, as well as a full suite of analysis tools. The Einstein Toolkit is currently based on the Cactus Framework for high-performance computing and the Carpet adaptive mesh refinement driver. It implements spacetime evolution via the BSSN evolution system and general-relativistic hydrodynamics in a finite-volume discretization. The toolkit is under continuous development and contains many new code components that have been publicly released for the first time and are described in this article. We discuss the motivation behind the release of the toolkit, the philosophy underlying its development, and the goals of the project. A summary of the implemented numerical techniques is included, as are results of numerical test covering a variety of sample astrophysical problems.

Abstract. We describe Cactus, a framework for building a variety of computing applications in science and engineering, including astrophysics, relativity and chemical engineering. We first motivate by example the need for such frameworks to support multi-platform, high performance applications across diverse communities. We then describe the design of the latest release of Cactus (Version 4.0) a complete rewrite of earlier versions, which enables highly modular, multi-language, parallel applications to be developed by single researchers and large collaborations alike. Making extensive use of abstractions, we detail how we are able to provide the latest advances in computational science, such as interchangeable parallel data distribution and high performance IO layers, while hiding most details of the underlying computational libraries from the application developer. We survey how Cactus 4.0 is being used by various application communities, and describe how it will also enable these applications to run on the computational Grids of the near future. Application Frameworks in Scientific ComputingVirtually all areas of science and engineering, as well as an increasing number of other fields, are turning to computational science to provide crucial tools to further their disciplines. The increasing power of computers offers unprecedented ability to solve complex equations, simulate natural and man-made complex processes, and visualise data, as well as providing novel possibilities such as new forms of art and entertainment. As computational power advances rapidly, computational tools, libraries, and computing paradigms themselves also advance. In such an environment, even experienced computational scientists and engineers can easily find themselves falling behind the pace of change, while they redesign and rework their codes to support the next computer architecture. This

We consider the perturbations of a relativistic star as an initial-value problem. Having discussed the formulation of the problem ͑the perturbation equations and the appropriate boundary conditions at the center and the surface of the star͒ in detail, we evolve the equations numerically from several different sets of initial data. In all the considered cases, we find that the resulting gravitational waves carry the signature of several of the star's pulsation modes. Typically, the fluid f mode, the first two p modes, and the slowest damped gravitational w mode are present in the signal. If such mode signals, from coalescing neutron stars or following a supernova, can be detected by future gravitational-wave antennae, one can hope to infer detailed information about neutron stars. Since a perturbation evolution should adequately describe the late time behavior of a dynamically excited neutron star, the present work can also be used as a benchmark test for future fully nonlinear simulations. ͓S0556-2821͑98͒01120-5͔ PACS number͑s͒: 04.40. Dg, 04.30.Ϫw, 95.30.Sf, 97.60.Jd