Introduction to Parallel Computing
A practical guide with examples in C
Author: Peter Arbenz and Wesley Petersen Series: Oxford Texts in Applied and Engineering Mathematics
This text is a practical student guide to scientific computing on parallel computers based on the author's lectures at ETH Zurich. 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.
A practical student guide to scientific computing on parallel computers, based on the authors' lectures at ETH Zurich. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, the subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations.
Hardcover
PRODUCT INFORMATION
Summary
This text is a practical student guide to scientific computing on parallel computers based on the author's lectures at ETH Zurich. 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.
A practical student guide to scientific computing on parallel computers, based on the authors' lectures at ETH Zurich. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, the subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations.
Description
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 ahardware 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.
About the Author
Peter Arbenz is at Institute for Scientific Computing, Department Informatik, ETHZ, Switzerland. Wesley Petersen is at Seminar for Applied Mathematics, Department of Mathematics, ETHZ, Switzerland.
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.
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