Parallel programming is facilitated by constructs which, unlike the widely used SPMD paradigm, provide programmers with a global view of the code and data structures. These constructs could be compiler directives containing information about data and task distribution, language extensions specifically designed for parallel computation, or classes that encapsulate parallelism. In this paper, we describe a class developed at Illinois and its MATLAB implementation. This class can be used to conveniently express both parallelism and locality. A C++ implementation is now underway. Its characteristics will be reported in a future paper. We have implemented most of the NAS benchmarks using our HTA MATLAB extensions and found during that HTAs enable the fast prototyping of parallel algorithms and produce programs that are easy to understand and maintain.