High throughput graphics processing unit based Fano decoder. (November 2016)

• Record Type: Journal Article
• Authors: Ates, Ozgur; Keskin, Selcuk; Kocak, Taskin
• Is Part Of: Journal of network and computer applications. Volume 75(2016)
• Page Start: 128
• Page End: 137
• Publication Date: 2016-11
• Subjects: Fano algorithm -- High throughput decoding -- Look-ahead -- Forward error correction (FEC) -- Compute unified device architecture (CUDA) -- KEPLER -- MAXWELL; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2016.08.020
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: The next-generation high speed wireless technologies, such as WirelessHD, bring the concept of several Gigabits per second data communication. However, forward error correction that takes place at the receiver side has become a real computational challenge. So far, only hardware solutions have offered such high-speed convolutional decoding, which could not be achieved by software solutions. Our paper aims to fill this gap and proposes a software level solution offering such multi-Gbps convolutional decoding. For this intend, we use the massively parallel computing power of NVIDIA GPGPUs and CUDA programming environment to implement a solution. As a decoding method, the Fano algorithm is selected for its relatively low memory requirements and computational complexity. A look-ahead mechanism and compact history in the form of circular queue is presented to support such high throughput. Conducted tests showed that our GPU based algorithm can decode up to 9.25 Gbps.