• DocumentCode
    13770
  • Title

    Energy-Efficient Pixel-Arithmetic

  • Author

    Zohaib Gilani, Syed ; Nam Sung Kim ; Schulte, Michael

  • Author_Institution
    Adv. Micro Devices, Markham, ON, Canada
  • Volume
    63
  • Issue
    8
  • fYear
    2014
  • fDate
    Aug. 1 2014
  • Firstpage
    1882
  • Lastpage
    1894
  • Abstract
    With the advent of pervasive computing, the performance requirements of visual applications have increased significantly. On the other hand, the energy budget for future devices may decrease due to reduced form factors and thus smaller battery sizes. It is thus imperative to improve energy efficiency of visual applications to meet their stringent demands in energy-constrained devices. This paper presents a novel energy-efficient floating-point unit (E 2FPU) that dynamically detects multiplications in which at least one operand is an integer power of two or the sum of consecutive integer powers of two (POW2 operands) and executes them on the E2FPU. We show that POW2 operands are extremely common in visual applications. For non-POW2 operands, we propose dynamic approximation of suitable operands as the closest POW2 operand with the same exponent while ensuring a small and limited approximation error. Finally, we exploit the limited dynamic range of pixel values to enhance the E2FPU to support low-energy FP addition for a sub-set of the single-precision floating-point dynamic range. The proposed E2 FPU can reduce execution energy by 35 percent with a negligible impact on the peak signal to noise ratio. Overall, at the chip-level, our approaches yield a 12 percent dynamic energy reduction for a graphics processing unit (GPU).
  • Keywords
    floating point arithmetic; graphics processing units; power aware computing; E2FPU; GPU; POW2 operands; approximation error; battery sizes; dynamic energy reduction; energy budget; energy efficiency; energy-constrained devices; energy-efficient floating-point unit; energy-efficient pixel-arithmetic; graphics processing unit; pervasive computing; single-precision floating-point dynamic range; visual applications; Approximation methods; Complexity theory; Energy consumption; Energy efficiency; Graphics processing units; Media; Pipelines; Energy efficiency; approximation; computer arithmetic; graphics processing unit (GPU); throughput processor;
  • fLanguage
    English
  • Journal_Title
    Computers, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9340
  • Type

    jour

  • DOI
    10.1109/TC.2014.2325827
  • Filename
    6819038