Introduction

It is not necessary to recall the dramatic increase in computer speed and the drop in cost of hardware over the last two decades. Today, anyone can buy a computer with which all of the programs in this book can be executed within a reasonable time – typically a few seconds to a few hours.

On the other hand, if there is one conclusion to be drawn from the enormous amount of research in computational physics, it should be that for most physical problems, a realistic treatment, one without severe approximations, is still not within reach. Quantum many-particle problems, for example, can only be treated if the correlations are treated in an approximate way (this does not hold for quantum Monte Carlo techniques, but there we suffer from minus-sign problems when treating fermions; see Chapter 12). It is easy to extend this list of examples.

Therefore the physical community always follows the developments in hardware and software with great interest. Developments in this area are so fast that if a particular type of machine were presented here as being today's state of the art, this statement would be outdated by the time the book is on the shelf. We therefore restrict ourselves here to a short account of some general principles of computer architecture and implications for software technology. The two main principles are pipelining and parallelism. Both concepts were developed a few decades ago, but pipelining became widespread in supercomputers from around 1980 and has found its way into most workstations, whereas parallelism has remained more restricted to the research community and to more expensive machines.