This book constitutes a carefully arranged selection of revised full papers chosen from the presentations given at the Second International Conference on Vector and Parallel Processing - Systems and Applications, VECPAR'96, held in Porto, Portugal, in September 1996. Besides 10 invited papers by internationally leading experts, 17 papers were accepted from the submitted conference papers for inclusion in this documentation following a second round of refereeing. A broad spectrum of topics and applications for which parallelism contributes to progress is covered, among them parallel linear algebra, computational fluid dynamics, data parallelism, implementational issues, optimization, finite element computations, simulation, and visualisation.

Unmatched: 50 Years of Supercomputing: A Personal Journey Accompanying the Evolution of a Powerful Tool The rapid and extraordinary progress of supercomputing over the past half-century is a powerful demonstration of our relentless drive to understand and shape the world around us. In this book, David Barkai offers a unique and compelling account of this remarkable technological journey, drawing from his own rich experiences working at the forefront of high-performance computing (HPC). This book is a journey delineated as five decade-long ‘epochs’ defined by the systems’ architectural themes: vector processors, multi-processors, microprocessors, clusters, and accelerators and cloud computing. The final part examines key issues of HPC and discusses where it might be headed. A central goal of this book is to show how computing power has been applied, and, more importantly, how it has impacted and benefitted society. To this end, the use of HPC is illustrated in a range of industries and applications, from weather and climate modeling to engineering and life sciences. As such, this book appeals to both students and general readers with an interest in HPC, as well as industry professionals looking to revolutionize their practice.

Compiling for parallelism is a longstanding topic of compiler research. This book describes the fundamental principles of compiling regular numerical programs for parallelism. We begin with an explanation of analyses that allow a compiler to understand the interaction of data reads and writes in different statements and loop iterations during program execution. These analyses include dependence analysis, use-def analysis and pointer analysis. Next, we describe how the results of these analyses are used to enable transformations that make loops more amenable to parallelization, and discuss transformations that expose parallelism to target shared memory multicore and vector processors. We then discuss some problems that arise when parallelizing programs for execution on distributed memory machines. Finally, we conclude with an overview of solving Diophantine equations and suggestions for further readings in the topics of this book to enable the interested reader to delve deeper into the field. Table of Contents: Introduction and overview / Dependence analysis, dependence graphs and alias analysis / Program parallelization / Transformations to modify and eliminate dependences / Transformation of iterative and recursive constructs / Compiling for distributed memory machines / Solving Diophantine equations / A guide to further reading