首页> 外文期刊>Journal of Theoretical and Applied Information Technology >SOLVING A PROBLEM OF RESOURCE-INTENSIVE MODELING OF DECODERS ON MASSIVELY PARALLEL COMPUTING DEVICES BASED ON VITERBI ALGORITHM
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SOLVING A PROBLEM OF RESOURCE-INTENSIVE MODELING OF DECODERS ON MASSIVELY PARALLEL COMPUTING DEVICES BASED ON VITERBI ALGORITHM

机译:基于维特比算法的大规模并行计算设备上的解码器资源密集型建模问题

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In this paper, we consider the problem of resource-intensive simulation of coding/decoding which corrects errors made at the preliminary stages of modern telecommunication system development. We propose to use the technology of parallel computing on GPU (GPGPU) to solve the problem of the process acceleration. We discuss the aspects of encoding/decoding simulation, which corrects errors in heterogeneous systems. The results of this technology applying in the convolutional codec parameters simulation, decoded by Viterbi algorithm, are given as well. Another problem concerned with limitation of the interaction speed with the computing device tail part and a random access to memory is also considered. We propose a solution by communication minimization at host-computing device level, as well as the use of caching. The simulation tools are described in the paper, including the use of computing technique of general purpose on GPU allowing to reduce the time required to optimize the noiseless coding system and thus for the development and implementation of telecommunication devices. We describe the solutions of tasks on codecs characteristics research using massively parallel computing, differing by simplified initialization of flow pseudorandom-number generator (PRNG) ensuring high performance with sufficient accuracy of calculations by reducing the number of calls to an external status register.
机译:在本文中,我们考虑了编码/解码的资源密集型仿真问题,该问题纠正了在现代电信系统开发的初期阶段所犯的错误。我们建议使用GPU上的并行计算技术(GPGPU)来解决进程加速问题。我们讨论了编码/解码仿真的各个方面,它们可以纠正异构系统中的错误。给出了该技术在卷积编解码器参数仿真中的应用结果,并通过维特比算法进行了解码。还考虑了与与计算设备尾部的交互速度的限制以及对存储器的随机访问有关的另一个问题。我们通过主机计算设备级别的通信最小化以及缓存的使用提出了一种解决方案。本文描述了仿真工具,包括在GPU上使用通用计算技术,从而减少了优化无噪声编码系统所需的时间,从而缩短了电信设备的开发和实现。我们描述了使用大规模并行计算进行编解码器特性研究的任务的解决方案,不同之处在于简化了流伪随机数生成器(PRNG)的初始化,从而通过减少对外部状态寄存器的调用次数来确保高性能和足够的计算精度。

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