  We introduce process-oriented programming as a natural extension of
object-oriented programming for parallel computing. It is based on the
observation that every class of an object-oriented language can be instantiated
as a process, accessible via a remote pointer. The introduction of process
pointers requires no syntax extension, identifies processes with programming
objects, and enables processes to exchange information simply by executing
remote methods. Process-oriented programming is a high-level language
alternative to multithreading, MPI and many other languages, environments and
tools currently used for parallel computations. It implements natural
object-based parallelism using only minimal syntax extension of existing
languages, such as C++ and Python, and has therefore the potential to lead to
widespread adoption of parallel programming. We implemented a prototype system
for running processes using C++ with MPI and used it to compute a large
three-dimensional Fourier transform on a computer cluster built of commodity
hardware components. Three-dimensional Fourier transform is a prototype of a
data-intensive application with a complex data-access pattern. The
process-oriented code is only a few hundred lines long, and attains very high
data throughput by achieving massive parallelism and maximizing hardware
utilization.
