FLASH is a publicly available high performance application code which has evolved into a modular, extensible software system from a collection of unconnected legacy codes. FLASH has been successful because its capabilities have been driven by the needs of scientific applications, without compromising maintainability, performance, and usability. In its newest incarnation, FLASH3 consists of inter-operable modules that can be combined to generate different applications. The FLASH architecture allows arbitrarily many alternative implementations of its components to co-exist and interchange with each other, resulting in greater flexibility. Further, a simple and elegant mechanism exists for customization of code functionality without the need to modify the core implementation of the source. A built-in unit test framework providing verifiability, combined with a rigorous software maintenance process, allow the code to operate simultaneously in the * Corresponding author dual mode of production and development. In this paper we describe the FLASH3 architecture, with emphasis on solutions to the more challenging conflicts arising from solver complexity, portable performance requirements, and legacy codes. We also include results from user surveys conducted in 2005 and 2007, which highlight the success of the code.

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Understanding the nature of turbulent flows remains one of the outstanding questions in classical physics. Significant progress has been recently made using computer simulation as an aid to our understanding of the rich physics of turbulence. Here, we present both the computer science and the scientific features of a unique terascale simulation of a weakly compressible turbulent flow that includes tracer particles. (Terascale refers to performance and dataset storage use in excess of a teraflop and terabyte, respectively.) The simulation was performed on the Lawrence Livermore National Laboratory IBM Blue Gene/Le system, using version 3 of the FLASH application framework. FLASH3 is a modular, publicly available code designed primarily for astrophysical simulations, which scales well to massively parallel environments. We discuss issues related to the analysis and visualization of such a massive simulation and present initial scientific results. We also discuss challenges related to making the database available for public release. We suggest that widespread adoption of an open dataset model of high-performance computing is likely to result in significant advantages for the scientific computing community, in much the same way that the widespread adoption of open-source software has produced similar gains over the last 10 years.

The FLASH code has evolved into a modular and extensible scientific simulation software system over the decade of its existence. During this time it has been cumulatively used by over a thousand researchers to investigate problems in astrophysics, cosmology, and in some areas of basic physics, such as turbulence. Recently, many new capabilities have been added to the code to enable it to simulate problems in high-energy density physics. Enhancements to these capabilities continue, along with enhancements enabling simulations of problems in fluid-structure interactions. The code started its life as an amalgamation of already existing software packages and sections of codes developed independently by various participating members of the team for other purposes. The code has evolved through a mixture of incremental and deep infrastructural changes. In the process, it has undergone four major revisions, three of which involved a significant architectural advancement. Along the way, a software process evolved that addresses the issues of code verification, maintainability, and support for the expanding user base. The software process also resolves the conflicts arising out of being in development and production simultaneously with multiple research projects, and between performance and portability. This paper describes the process of code evolution with emphasis on the design decisions and software management policies that have been instrumental in the success of the code. The paper also makes the case for a symbiotic relationship between scientific research and good software engineering of the simulation software.