Introduction to High-Performance Simulation

Tutorial at ESS 99 by
Graham Horton
University of Erlangen-Nuremberg, Dept. of Computer Science X

Martensstrasse 3, 91058 Erlangen
e-mail: horton@informatik.uni-erlangen.de

 

Almost all very-large-scale computations are simulations of natural phenomena or technical systems. In addition, the problems to be solved - such as the "Grand Challenge" problems are often of significant scientific, economic or social importance. Their complexity is such that they can require impractically long computation times even on the fastest available computers.
The field of high-performance simulation addresses this situation by seeking new techniques for reducing the computation time for important classes of simulation problems. There are essentially three main approaches to achieving this, which will all be covered in the tutorial.
The first and most obvious approach is to perform the simulations on faster computers. This almost always involves a more or less substantial reformulation of the simulation algorithm and perhaps even a complete re-design and re-coding of the program. This is particularly true for high-performance parallel computers. Modern parallel supercomputers now offer a performance in the Teraflop range and even workstation clusters can yield aggregate performances in the 10GFLOPS range. In the tutorial we will therefore examine common techniques and pitfalls involved in parallel simulation.
Secondly, new, faster algorithms can be developed, which achieve a direct reduction in the computational complexity of the simulation problem. Techniques such as multi-level algorithms have, for example, in recent years, given rise to orders-of-magnitude performance improvements for many kinds of simulation problems. We will therefore examine these and other techniques for developing faster simulation algorithms.
Finally, a given simulation program can be tuned to achieve maximum performance on a particular computer or class of computers. This tuning can involve the reorganisation of code, the reorganisation of data or the reorganisation of the underlying algorithm. In the tutorial we will explain the basic architectural principles of modern computers and show how to improve simulation progrmas to derive maximum performance from them. Examples will be given demonstrating the significant performance benefits that can be achieved - often by relatively simple means.