The design and implementation of a region-based parallel programming language

Programming parallel computers is an extremely challenging task for expert computer programmers, let alone for scientists in other disciplines whose computations often drive the acquisition of such machines. This dissertation describes the design and implementation of ZPL, a programming language created to simplify the task of programming parallel computers. ZPL allows programmers to write code using a global view that describes their algorithms at a high level rather than implementing per-processor behavior. However, unlike other global-view languages, ZPL permits users to reason about the parallel implementation of their code at the syntactic level, allowing them to make informed algorithmic decisions based on the program's parallel implementation. The language feature that supports this duality is called the region. A region is simply a language-level index set that programmers can define, name, and manipulate using high-level operators. Regions constitute a unique means of specifying array computation, serving as an alternative to traditional array indexing and slicing. By distributing each region's indices across a processor set, a parallel interpretation of a ZPL program is achieved. This dissertation studies the impact of the region concept throughout the design and implementation of ZPL. It begins by defining the region concept and its use in the language. It then gives a parallel interpretation of regions, which results in ZPL's syntax-based performance model. ZPL's implementation and runtime libraries are described in detail to show how regions are represented and used at runtime. The design and implementation of a paradigm-neutral interface for efficient portable communication is also described. Finally, two extensions to the basic region concept are given: parameterized regions which can be used to implement hierarchical algorithms such as the multigrid method, and sparse regions which can be used to specify sparse computation over sparse or dense arrays. Throughout the dissertation, regions are evaluated by comparing ZPL programs to other languages in terms of clarity and performance. The conclusion is that regions are a crisp and powerful mechanism for array-based parallel programming.