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New Algorithms for High-Throughput Decoding with Low-Density Parity-Check Codes using Fixed-Point SIMD Processors.

机译:使用定点SIMD处理器的低密度奇偶校验码高通量解码的新算法。

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摘要

Most digital signal processors contain one or more functional units with a single-instruction, multiple-data architecture that supports saturating fixed-point arithmetic with two or more options for the arithmetic precision. The processors designed for the highest performance contain many such functional units connected through an on-chip network. The selection of the arithmetic precision provides a trade-off between the task-level throughput and the quality of the output of many signal-processing algorithms, and utilization of the interconnection network during execution of the algorithm introduces a latency that can also limit the algorithm's throughput.;In this dissertation, we consider the turbo-decoding message-passing algorithm for iterative decoding of low-density parity-check codes and investigate its performance in parallel execution on a processor of interconnected functional units employing fast, low-precision fixed-point arithmetic. It is shown that the frequent occurrence of saturation when 8-bit signed arithmetic is used severely degrades the performance of the algorithm compared with decoding using higher-precision arithmetic. A technique of limiting the magnitude of certain intermediate variables of the algorithm, the extrinsic values, is proposed and shown to eliminate most occurrences of saturation, resulting in performance with 8-bit decoding nearly equal to that achieved with higher-precision decoding.;We show that the interconnection latency can have a significant detrimental effect of the throughput of the turbo-decoding message-passing algorithm, which is illustrated for a type of high-performance digital signal processor known as a stream processor. Two alternatives to the standard schedule of message-passing and parity-check operations are proposed for the algorithm. Both alternatives markedly reduce the interconnection latency, and both result in substantially greater throughput than the standard schedule with no increase in the probability of error.
机译:大多数数字信号处理器包含一个或多个具有单指令多数据架构的功能单元,该架构支持饱和定点运算,并具有两个或多个选项以提高运算精度。为实现最高性能而设计的处理器包含许多通过片上网络连接的功能单元。算术精度的选择在任务级吞吐量和许多信号处理算法的输出质量之间进行了折衷,算法执行过程中对互连网络的利用引入了等待时间,这也可能会限制算法的处理能力。在本文中,我们考虑了用于低密度奇偶校验码的迭代解码的Turbo解码消息传递算法,并研究了它在采用快速,低精度固定值的互连功能单元的处理器上并行执行的性能。点算术。结果表明,与使用高精度算法进行解码相比,使用8位有符号算法时频繁发生饱和会严重降低算法的性能。提出并限制了算法的某些中间变量(外部值)的大小的技术,该技术可消除大多数饱和现象,从而使8位解码的性能几乎与采用高精度解码实现的性能相同。显示了互连等待时间可能会对Turbo解码消息传递算法的吞吐量产生重大不利影响,该算法针对一种称为流处理器的高性能数字信号处理器进行了说明。针对该算法,提出了消息传递和奇偶校验操作的标准调度的两种选择。两种选择都显着减少了互连延迟,并且两种方法都导致吞吐量比标准调度程序大得多,而不会增加出错的可能性。

著录项

  • 作者

    Kennedy, JaWone Anthony.;

  • 作者单位

    Clemson University.;

  • 授予单位 Clemson University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 115 p.
  • 总页数 115
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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