Paper Info
Title
Implementation of a High Throughput 3GPP Turbo Decoder on GPU
Abstract
Turbo code is a computationally intensive channel code that is widely used in current and upcoming wireless standards. General-purpose graphics processor unit聽(GPGPU) is a programmable commodity processor that achieves high performance computation power by using many simple cores. In this paper, we present a 3GPP LTE compliant Turbo decoder accelerator that takes advantage of the processing power of GPU to offer fast Turbo decoding throughput. Several techniques are used to improve the performance of the decoder. To fully utilize the computational resources on GPU, our decoder can decode multiple codewords simultaneously, divide the workload for a single codeword across multiple cores, and pack multiple codewords to fit the single instruction multiple data聽(SIMD) instruction width. In addition, we use shared memory judiciously to enable hundreds of concurrent multiple threads while keeping frequently used data local to keep memory access fast. To improve efficiency of the decoder in the high SNR regime, we also present a low complexity early termination scheme based on average extrinsic LLR statistics. Finally, we examine how different workload partitioning choices affect the error correction performance and the decoder throughput.
Year
DOI
Venue
2011
10.1007/s11265-011-0617-7
Signal Processing Systems
Keywords
Field
DocType
GPGPU,Turbo decoding,Accelerator,Parallel computing,Wireless,Error control codes,Turbo codes
Shared memory,Computer science,Turbo code,Serial concatenated convolutional codes,Parallel computing,SIMD,Real-time computing,Error detection and correction,Turbo equalizer,General-purpose computing on graphics processing units,Soft-decision decoder
Journal
Volume
Issue
ISSN
65
2
1939-8018
Citations 
PageRank 
References 
25
1.30
18
Authors
4
Name
Order
Citations
PageRank
Michael Wu127118.30
Yang Sun237824.59
Guohui Wang3108860.78
Joseph R. Cavallaro41175115.35