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Efficient evaluation methods of elementary functions suitable for SIMD computation

机译:适用于SIMD计算的基本函数的有效评估方法

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摘要

Data-parallel architectures like SIMD (Single Instruction Multiple Data) or SIMT (Single Instruction Multiple Thread) have been adopted in many recent CPU and GPU architectures. Although some SIMD and SIMT instruction sets include double-precision arithmetic and bitwise operations, there are no instructions dedicated to evaluating elementary functions like trigonometric functions in double precision. Thus, these functions have to be evaluated one by one using an FPU or using a software library. However, traditional algorithms for evaluating these elementary functions involve heavy use of conditional branches and/or table look-ups, which are not suitable for SIMD computation. In this paper, efficient methods are proposed for evaluating the sine, cosine, arc tangent, exponential and logarithmic functions in double precision without table lookups, scattering from, or gathering into SIMD registers, or conditional branches. We implemented these methods using the Intel SSE2 instruction set to evaluate their accuracy and speed. The results showed that the average error was less than 0.67 ulp, and the maximum error was 6 ulps. The computation speed was faster than the FPUs on Intel Core 2 and Core i7 processors.
机译:诸如SIMD(单指令多数据)或SIMT(单指令多线程)之类的数据并行架构已在许多最近的CPU和GPU架构中采用。尽管某些SIMD和SIMT指令集包括双精度算术和按位运算,但没有专门用于以双精度评估诸如三角函数之类的基本函数的指令。因此,必须使用FPU或使用软件库逐一评估这些功能。但是,用于评估这些基本功能的传统算法需要大量使用条件分支和/或表查找,而这不适用于SIMD计算。在本文中,提出了一种有效的方法来以双精度评估正弦,余弦,反正切,指数和对数函数,而无需进行表查找,从SIMD寄存器或条件分支中散布或聚集到SIMD寄存器中。我们使用Intel SSE2指令集实施了这些方法,以评估其准确性和速度。结果表明,平均误差小于0.67 ulp,最大误差为6 ulps。计算速度比Intel Core 2和Core i7处理器上的FPU更快。

著录项

  • 来源
    《Computer science》 |2010年第2期|25-32|共8页
  • 作者

    Naoki Shibata;

  • 作者单位

    Department of Information Processing & Management, Shiga University, 1-1-1 Bamba, Hikone 522-8522, Japan;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    SIMD; elementary functions;

    机译:SIMD;基本功能;

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