A design methodology for data-parallel applications

A methodology for the design and development of data-parallel applications and components is presented. Data-parallelism is a well understood form of parallel computation, yet developing simple applications can involve substantial efforts to express the problem in low level notations. We describe a process of software development for data-parallel applications starting from high level specifications, generating repeated refinements of designs to match different architectural models and performance constraints, enabling a development activity with cost benefit analysis. Primary issues are algorithm choice, correctness, and efficiency, followed by data decomposition, load balancing, and message passing coordination. Development of a data-parallel multitarget tracking application is used as a case study, showing the progression from high to low level refinements. We conclude by describing tool support for the process.