The goal of this work is to simplify parallel application development, and thus ease the learning barriers faced by non-experts. It is especially useful where there is little data-parallelism to be recognized by a compiler. The applications programmer need learn the intricacies of only one primary subroutine in order to get the full benefits of the parallel interface. The applications programmer defines a high level concept, the task, that depends only on his application, and not on any particular parallel library. The task is defined by its three phases: (a) the task input, (b) sequential code to execute the task, and (c) any modifications of global variables that occur as a result of the task. In particular, side effects (which change global variable values) must not occur in phase (b). Forcing the user to re-organize his computation in these terms allows us to present the applications programmer with a single global environment visible to all processors (whether on a SMP or a NOW architecture), in the context of a masterslave architecture. Both a shared memory implementation (running on an SGI or SUN Solaris architecture) and a NOW memory implementation (running on top of MPI) are described. The implementations were tested by a naive program for integer factorization, and by a more sophisticated Todd-Coxeter coset enumeration. Integer factorization was chosen so as to exercise the major features of TOP-C in an unambiguous context.