Engineering a Parallel Compiler for Standard Ml

We present the design and partial implementation of an automated parallelising compiler for Standard ML using algorithmic skeletons. Source programs are parsed and elaborated using the ML Kit compiler and a small set of higher order functions are automatically detected and replaced with parallel equivalents. Without the presence of performance predictions, the compiler simply instantiates all instances of the known HOFs with parallel equivalents. The resulting SML program is then output as Objective Caml and compiled with the parallel skeleton harnesses giving an exe-cutable which runs on networks of workstations. The parallel harnesses are implemented in C with MPI providing the communications subsystem. A substantial parallel exemplar is presented, an implementation of the Canny edge tracking algorithm from computer vision which is parallelised by implementing the map skeleton over a set of subimages.