In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich, is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines, and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and, in some cases, Fortran. This book is also ideal for practitioners and programmers.The contents of this book are a distillation of many projects which have subsequentlybecome the material for a course on parallel computing given for severalyears at the Swiss Federal Institute of Technology in Z¨urich. Students in thiscourse have typically been in their third or fourth year, or graduate students,and have come from computer science, physics, mathematics, chemistry, and programsfor computational science and engineering. Student contributions, whetherlarge or small, critical or encouraging, have helped crystallize our thinking in aquickly changing area. It is, alas, a subject which overlaps with all scientificand engineering disciplines. Hence, the problem is not a paucity of material butrather the distillation of an overflowing cornucopia. One of the students’ mostoften voiced complaints has been organizational and of information overload. It isthus the point of this book to attempt some organization within a quickly changinginterdisciplinary topic. In all cases, we will focus our energies on floatingpoint calculations for science and engineering applications.
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