Preface

Summary

This book is about ways of developing software that can be executed by parallel computers. Software is one of the most complex and difficult artefacts that humans build. Parallelism increases this complexity significantly. At the moment, parallel software is designed for specific kinds of architectures, and can only be moved from architecture to architecture by large-scale rewriting. This is so expensive that very few applications have been discovered for which the effort is worth it. These are mostly numeric and scientific.

I am convinced that the only way to move beyond this state of affairs and use parallelism in a wide variety of applications is to break the tight connection between software and hardware. When this is done, software can be moved with greater ease from architecture to architecture as new ones are developed or become affordable. One of the main claims of this book is that it is possible to do this while still delivering good performance on all architectures, although not perhaps the optimal wall-clock performance that obsesses the present generation of parallel programmers.

The approach presented in this book is a generalisation of abstract data types, which introduced modularity into software design. It is based on categorical data types, which encapsulate control flow as well as data representation. The semantics of powerful operations on a data type are decoupled from their implementation. This allows a variety of implementations, including parallel ones, without altering software.