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VALU, AVX and GPU Acceleration Techniques for Parallel FDTD Methods [Hardcover]

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  • Category: Books (Computers)
  • Author:  Yu, Wenhua, Yang, Xiaoling, Li, Wenxing
  • Author:  Yu, Wenhua, Yang, Xiaoling, Li, Wenxing
  • ISBN-10:  1613531745
  • ISBN-10:  1613531745
  • ISBN-13:  9781613531747
  • ISBN-13:  9781613531747
  • Publisher:  Scitech Publishing
  • Publisher:  Scitech Publishing
  • Pages:  248
  • Pages:  248
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Mar-2013
  • Pub Date:  01-Mar-2013
  • SKU:  1613531745-11-MPOD
  • SKU:  1613531745-11-MPOD
  • Item ID: 101230495
  • List Price: $130.00
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Sep 28 to Sep 30
  • Notes: Brand New Book. Order Now.

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.

US

Combining complex electromagnetic problems with computer science techniques, this book introduces a general hardware acceleration technique that can significantly speed up FDTD simulations and their applications to engineering problems without requiring any additional hardware devices.

  • 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
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