This book is a practical guide to performance optimization of computationally intensive programs on Sun UltraSPARC platforms. It is primarily intended for developers of technical or HPC applications for Solaris Operating Environment. This audience includes both independent software vendor (ISV) developers and noncommercial developers. It can also be used by end-users of HPC applications to help them better understand how applications utilize system resources.

The book presents information so that it follows logical stages of the process for application development and optimization. We pay special attention to issues related to parallel applications and to using appropriate performance measurement tools. Wherever applicable, sections are illustrated with code examples that show benefits of methods described.

Unless otherwise noted, topics in this book are not limited to a particular programming language, parallelization method, software version, or hardware product. However, emphasis is on techniques relevant to applications written in Fortran 77, Fortran 90, and C, because these languages are most commonly used in HPC and technical applications. Most topics can be applied to C++ programs, however, we do not address performance optimization issues specific to object oriented programming.

ABOUT THE AUTHORS

Rajat P. Garg is a staff engineer in the Performance Technologies Group at Sun Microsystems, Inc. where he works on compiler performance analysis and benchmarking. Prior to that, he worked in the Market Development Engineering group, optimizing third-party scientific and technical applications on Sun's UltraSPARC systems. He has published over a dozen articles in peer-reviewed technical journals and conferences, and has three US patents pending. He obtained a PhD degree in Mechanical Engineering from Stanford University, Palo Alto, California, in 1996.

Ilya Sharapov is a member of the Market Development Engineering group at Sun Microsystems, Inc. where he works on performance analysis and optimization of applications for mechanical computer-aided engineering, computational chemistry, and bioinformatics. He has published a number of papers on software engineering and optimization. He received his PhD degree in Mathematics from the University of California, Los Angeles, California, in 1997.