Simulation of LDPC convolutional decoders with CPU and GPU

Chi H. Chan; Chung Ming Lau

doi:10.1109/CECNet.2012.6202062

Simulation of LDPC convolutional decoders with CPU and GPU

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

Abstract

In this paper, the Sum Product Algorithm (SPA) and the Min-Sum Algorithm (MSA) are used for decoding low-density parity-check convolutional codes (LDPC-CCs). The two algorithms have been implemented and run on three different computing environments. The first environment is a single-threading Central Processing Unit (CPU); the second one is the multi-threading CPU based on OpenMP (Open Multi-Processing); and the third one is the multi-threading Graphics Processing Unit (GPU). The error performance of the LDPC-CCs and the simulation time taken under the three specific computing environments and the two decoding algorithms are evaluated and compared. It is found that the different computing environments produce very similar error results. It is also concluded that using the GPU computing platform can reduce the simulation time substantially.

Original language	English
Title of host publication	2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings
Pages	2854-2857
Number of pages	4
DOIs	https://doi.org/10.1109/CECNet.2012.6202062
Publication status	Published - 11 Jun 2012
Event	2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Three Gorges, China Duration: 21 Apr 2012 → 23 Apr 2012

Conference

Conference	2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012
Country/Territory	China
City	Three Gorges
Period	21/04/12 → 23/04/12

Keywords

CPU
error-correction code
GPU
LDPC convolutional code
OpenMP

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering

More information

10.1109/CECNet.2012.6202062

Cite this

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title = "Simulation of LDPC convolutional decoders with CPU and GPU",

abstract = "In this paper, the Sum Product Algorithm (SPA) and the Min-Sum Algorithm (MSA) are used for decoding low-density parity-check convolutional codes (LDPC-CCs). The two algorithms have been implemented and run on three different computing environments. The first environment is a single-threading Central Processing Unit (CPU); the second one is the multi-threading CPU based on OpenMP (Open Multi-Processing); and the third one is the multi-threading Graphics Processing Unit (GPU). The error performance of the LDPC-CCs and the simulation time taken under the three specific computing environments and the two decoding algorithms are evaluated and compared. It is found that the different computing environments produce very similar error results. It is also concluded that using the GPU computing platform can reduce the simulation time substantially.",

keywords = "CPU, error-correction code, GPU, LDPC convolutional code, OpenMP",

author = "Chan, {Chi H.} and Lau, {Chung Ming}",

year = "2012",

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day = "11",

doi = "10.1109/CECNet.2012.6202062",

language = "English",

isbn = "9781457714153",

pages = "2854--2857",

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note = "2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 ; Conference date: 21-04-2012 Through 23-04-2012",

}

Chan, CH & Lau, CM 2012, Simulation of LDPC convolutional decoders with CPU and GPU. in 2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings., 6202062, pp. 2854-2857, 2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012, Three Gorges, China, 21/04/12. https://doi.org/10.1109/CECNet.2012.6202062

Simulation of LDPC convolutional decoders with CPU and GPU. / Chan, Chi H.; Lau, Chung Ming.
2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings. 2012. p. 2854-2857 6202062.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

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AU - Chan, Chi H.

AU - Lau, Chung Ming

PY - 2012/6/11

Y1 - 2012/6/11

N2 - In this paper, the Sum Product Algorithm (SPA) and the Min-Sum Algorithm (MSA) are used for decoding low-density parity-check convolutional codes (LDPC-CCs). The two algorithms have been implemented and run on three different computing environments. The first environment is a single-threading Central Processing Unit (CPU); the second one is the multi-threading CPU based on OpenMP (Open Multi-Processing); and the third one is the multi-threading Graphics Processing Unit (GPU). The error performance of the LDPC-CCs and the simulation time taken under the three specific computing environments and the two decoding algorithms are evaluated and compared. It is found that the different computing environments produce very similar error results. It is also concluded that using the GPU computing platform can reduce the simulation time substantially.

AB - In this paper, the Sum Product Algorithm (SPA) and the Min-Sum Algorithm (MSA) are used for decoding low-density parity-check convolutional codes (LDPC-CCs). The two algorithms have been implemented and run on three different computing environments. The first environment is a single-threading Central Processing Unit (CPU); the second one is the multi-threading CPU based on OpenMP (Open Multi-Processing); and the third one is the multi-threading Graphics Processing Unit (GPU). The error performance of the LDPC-CCs and the simulation time taken under the three specific computing environments and the two decoding algorithms are evaluated and compared. It is found that the different computing environments produce very similar error results. It is also concluded that using the GPU computing platform can reduce the simulation time substantially.

KW - CPU

KW - error-correction code

KW - GPU

KW - LDPC convolutional code

KW - OpenMP

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BT - 2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings

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Y2 - 21 April 2012 through 23 April 2012

ER -

Simulation of LDPC convolutional decoders with CPU and GPU

Abstract

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Keywords

ASJC Scopus subject areas

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