替换和简化:近似和高质量可配置电路的统一设计范例

Swagath Venkataramani, K. Roy, A. Raghunathan
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引用次数: 161

摘要

许多应用程序对其底层计算中的不精确或近似具有固有的弹性。近似电路设计是一种新兴的范例,它利用这种固有的弹性来实现在能源或性能上高效的硬件实现。在这项工作中,我们提出了替代和简化(SASIMI),一种新的系统方法来设计和合成近似电路。SASIMI背后的关键见解是识别电路中假设相同值的高概率信号对,并用一个替换另一个。虽然这些替换引入了功能近似,但如果执行得当,它们会导致从电路中消除一些逻辑,同时还可以缩小关键路径上的门(简化),从而显著节省功耗。我们提出了一个自动合成框架,迭代地执行替换和简化,同时确保满足用户指定的质量约束。我们扩展了所提出的框架,以执行高质量可配置电路的自动合成,这些电路可以根据应用需求以不同的精度水平动态运行。我们使用SASIMI自动合成各种算术单元(加法器,乘数器,MAC),复杂数据路径(SAD, FFT蝴蝶,欧氏距离)和ISCAS85基准的近似和质量可配置实现,使用各种错误度量,如错误率和平均错误幅度。综合近似电路在严格误差约束下的功耗提高了10% ~ 28%,在宽松误差约束下的功耗提高了30% ~ 60%。质量可配置电路在近似模式下获得14%-40%的能量改进,而在精确模式下不产生能量开销。
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Substitute-and-simplify: A unified design paradigm for approximate and quality configurable circuits
Many applications are inherently resilient to inexactness or approximations in their underlying computations. Approximate circuit design is an emerging paradigm that exploits this inherent resilience to realize hardware implementations that are highly efficient in energy or performance. In this work, we propose Substitute-And-SIMplIfy (SASIMI), a new systematic approach to the design and synthesis of approximate circuits. The key insight behind SASIMI is to identify signal pairs in the circuit that assume the same value with high probability, and substitute one for the other. While these substitutions introduce functional approximations, if performed judiciously, they result in some logic to be eliminated from the circuit while also enabling downsizing of gates on critical paths (simplification), resulting in significant power savings. We propose an automatic synthesis framework that performs substitution and simplification iteratively, while ensuring that a user-specified quality constraint is satisfied. We extend the proposed framework to perform automatic synthesis of quality configurable circuits that can dynamically operate at different accuracy levels depending on application requirements. We used SASIMI to automatically synthesize approximate and quality configurable implementations of a wide range of arithmetic units (Adders, Multipliers, MAC), complex data paths (SAD, FFT butterfly, Euclidean distance) and ISCAS85 benchmarks, using various error metrics such as error rate and average error magnitude. The synthesized approximate circuits demonstrate power improvements of 10%–28% for tight error constraints, and 30%–60% for relaxed error constraints. The quality configurable circuits obtain between 14%–40% improvement in energy in the approximate mode, while incurring no energy overheads in the accurate mode.
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