Runtime Accuracy-Configurable Approximate Hardware Synthesis Using Logic Gating and Relaxation

Tanfer Alan, A. Gerstlauer, J. Henkel
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引用次数: 4

Abstract

Approximate computing trades off computation accuracy against energy efficiency. Algorithms from several modern application domains such as decision making and computer vision are tolerant to approximations while still meeting their requirements. The extent of approximation tolerance, however, significantly varies with a change in input characteristics and applications.We propose a novel hybrid approach for the synthesis of runtime accuracy configurable hardware that minimizes energy consumption at area expense. To that end, first we explore instantiating multiple hardware blocks with different fixed approximation levels. These blocks can be selected dynamically and thus allow to configure the accuracy during runtime. They benefit from having fewer transistors and also synthesis relaxations in contrast to state-of-the-art gating mechanisms which only switch off a group of logic. Our hybrid approach combines instantiating such blocks with area-efficient gating mechanisms that reduce toggling activity, creating a fine-grained design-time knob on energy vs. area. Examining total energy savings for a Sobel Filter under different workloads and accuracy tolerances show that our method finds Pareto-optimal solutions providing up to 16% and 44% energy savings compared to state-of-the-art accuracy-configurable gating mechanism and an exact hardware block, respectively, at 2x area cost.
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运行时精度-使用逻辑门控和松弛的可配置近似硬件合成
近似计算权衡了计算精度和能源效率。一些现代应用领域的算法,如决策和计算机视觉,在满足其要求的同时对近似具有容忍度。然而,近似公差的范围随着输入特性和应用的变化而显著变化。我们提出了一种新的混合方法,用于合成运行时精度可配置硬件,以最大限度地减少能耗。为此,我们首先探索实例化具有不同固定近似级别的多个硬件块。可以动态地选择这些块,从而允许在运行时配置准确性。与只关闭一组逻辑的最先进的门控机制相比,它们的优点是拥有更少的晶体管和合成弛豫。我们的混合方法结合了实例化这样的块和面积有效的门控机制,减少了切换活动,创建了一个细粒度的能量与面积的设计时间钮。在不同工作负载和精度公差下,对Sobel过滤器的总节能进行了检查,结果表明,与最先进的可精确配置的门控机制和精确的硬件块相比,我们的方法发现帕累托最优解决方案分别提供了高达16%和44%的节能,面积成本分别为2倍。
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