ScholarLens Back to search
2009•Digest - IEEE Antennas and Propagation Society. International SymposiumRequires access

High-speed FDTD simulation algorithm for GPU with compute unified device architecture

Naoki Takada, Tomoyoshi Shimobaba, Nobuyuki Masuda, Tomoyoshi Ito

Open publisher page 19 citations

Abstract

In this paper, we propose a high-speed FDTD algorithm for GPU. Our algorithm includes two important techniques: coalesced global memory access on a GPU board and the improved cache block algorithm for GPU which resembles that for the central processing unit (CPU). Our algorithm achieved an approximately 20- fold improvement in computational speed compared with a conventional CPU at the maximum computational speed of the GPU.

About this research paper

What this paper is about

In this paper, we propose a high-speed FDTD algorithm for GPU. Our algorithm includes two important techniques: coalesced global memory access on a GPU board and the improved cache block algorithm for GPU which resembles that for the central processing unit (CPU). Our algorithm achieved an approximately 20- fold improvement in computational speed compared with a conventional CPU at the maximum computational speed of the GPU.

Why it matters

OpenAlex reports 19 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In this paper, we propose a high-speed FDTD algorithm for GPU. Our algorithm includes two important techniques: coalesced global memory access on a GPU board and the improved cache block algorithm for GPU which resembles that for the central processing unit (CPU). Our algorithm achieved an approximately 20- fold improvement in computational speed compared with a conventional CPU at the maximum computational speed of the GPU.

Key concepts: Computer science, Parallel computing, CUDA, Central processing unit, Speedup, Block (permutation group theory), Graphics processing unit, Computational science

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
High-speed FDTD simulation algorithm for GPU with compute unified device architecture — Research Paper | ScholarLens