Programming is hard. Building a large program is like constructing a steam locomotive
through a hole the size of a postage stamp. An artefact that is the fruit of hundreds of person …

Building a cost calculus for a parallel program development environment is difficult because
of the many degrees of freedom available in parallel implementations and because of …

Data parallelism is often seen as a form of explicit parallelism for SIMD and vector machines,
and data parallel programming as an explicit programming paradigm for these architectures …

Programming irregular and dynamic data-parallel algorithms must consider the effect of data
distribution. The implementation of a load balancing algorithm is quite a difficult task for the …

Software itself may be considered a formal structure and may be subject to mathematical
analysis. This leads to a discipline of formal software engineering (which is not necessarily …

Call a parallel program p-independent if and only if it always produces the same output on
the same input regardless of the number or arrangement of (virtual) processors on which it is …

We derive a provably correct, architecture-independent family of parallel implementations for
a class of data-parallel algorithms, called DH (distributable homomorphisms). The …

We present a proof system for a simple data-parallel kernel language called L. This proof
system is based on a two-component assertion language. We define a weakest …

Parallel programming faces two major challenges: how to efficiently map computations to
different parallel hardware architectures, and how to do it in a modular way, ie, without …

An approach, called SAT (Stages And Transformations), is introduced to support the
derivation of parallel distributed-memory programs. During the design, a program is viewed …