Parallel LDPC decoding on a GPU using OpenCL and global memory for accelerators

Citations

SCOPUS

4

초록

This paper introduces a parallel software decoder of Low Density Parity Check (LDPC) codes with an Open Computing Language (OpenCL) framework including Global Memory for ACcelerators (GMAC). The LDPC code is one of the most popular and strongest error correcting codes for mobile communication systems. OpenCL is an open standard programming framework that supports programming languages and application programming interfaces (APIs) for heterogeneous platforms. GMAC is a software implementation of Asymmetric Distributed Shared Memory (ADSM) that maintains a shared logical memory space for the host to access memory objects in the physical memory of an OpenCL device. In this paper, we parallelize the iterative LDPC decoding steps on a graphics processing unit (GPU) using OpenCL. To improve the performance of the proposed decoder, data transfer optimization techniques between the host and the GPU including pre-pinned OpenCL memory objects for GMAC are applied. In terms of the entire decoding time, the speedup of the proposed LDPC decoder over a conventional OpenCL implementation is 1.28.

키워드

GMACLDPC decoderOpenCLApplication programming interfaces (API)Codes (symbols)Computational linguisticsComputer graphicsComputer graphics equipmentData transferDecodingDigital storageForward error correctionInformation theoryIterative decodingIterative methodsMobile telecommunication systemsProgram processorsRadio broadcastingSatellite communication systemsData transfer optimizationsDistributed shared memoryGMACGraphics Processing UnitLDPC decoderLow-density parity-check (LDPC) codesOpenCLSoftware implementationMemory architecture
제목
Parallel LDPC decoding on a GPU using OpenCL and global memory for accelerators
저자
Hong, Jung-HyunChung, Ki-Seok
DOI
10.1109/NAS.2015.7255228
발행일
2015-08
유형
Conference Paper
저널명
Proceedings of the 2015 IEEE International Conference on Networking, Architecture and Storage, NAS 2015
페이지
353 ~ 354