VALU, AVX and GPU Acceleration Techniques for Parallel FDTD Methods

by Wenhua Yu, Xiaoling Yang, Wenxing Li

Overview

Development of computer science techniques has significantly enhanced computational electromagnetic methods in recent years. The multi-core CPU computers and multiple CPU work stations are popular today for scientific research and engineering computing. How to achieve the best performance on the existing hardware platforms, however, is a major challenge. In addition to the multi-core computers and multiple CPU workstations, distributed computing has become a primary trend due to the low cost of the hardware and the high performance of network systems. In this book we introduce a general hardware acceleration technique that can significantly speed up FDTD simulations and their applications to engineering problems without requiring any additional hardware devices.

Product Details

ISBN-13:	9781613531747
Publisher:	The Institution of Engineering and Technology
Publication date:	09/23/2013
Series:	Computing and Networks
Pages:	248
Product dimensions:	7.20(w) x 10.20(h) x 0.80(d)

About the Author

Dr Wenhua Yu has worked on the topics related to FDTD method, software development techniques, parallel processing techniques, and engineering applications for many years, and has published more than 150 technical papers and six books on the parallel FDTD methods and simulation techniques. Dr. Wenhua Yu is the general co-chair of several international conferences on the topic of computational electromagnetics, antennas and microwave circuits. Dr. Wenhua Yu is a senior member of IEEE.

Along with Dr Wenhua Yu, Mr Xiaoling Yang are the primary developers of the GEMS software package.

Prof. Wenxing Li is an expert in the computational electromagnetic method, antenna design, and electromagnetic compatibility.

Table of Contents

• Chapter 1: Introduction to the Parallel FDTD Method
• Chapter 2: VALU/AVX Acceleration Techniques
• Chapter 3: PML Acceleration Techniques
• Chapter 4: Parallel Processing Techniques
• Chapter 5: GPU Acceleration Techniques
• Chapter 6: Engineering Applications
• Chapter 7: Cloud ComputingTechniques
• Appendix: 3-D Parallel FDTD Source Code