Parametric Yield-Driven Resource Binding in High-Level Synthesis with Multi-Vth/VddLibrary and Device Sizing

Author:

Chen Yibo1,Wang Yu2,Xie Yuan1,Takach Andres3

Affiliation:

1. Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA

2. Department of Electronics Engineering, Tsinghua University, Beijing 100084, China

3. Design Creation and Synthesis, Mentor Graphics Corporation, Wilsonville, OR 97070, USA

Abstract

The ever-increasing chip power dissipation in SoCs has imposed great challenges on today’s circuit design. It has been shown that multiple threshold and supply voltages assignment (multi-Vth/Vdd) is an effective way to reduce power dissipation. However, most of the prior multi-Vth/Vddoptimizations are performed under deterministic conditions. With the increasing process variability that has significant impact on both the power dissipation and performance of circuit designs, it is necessary to employ statistical approaches in analysis and optimizations for low power. This paper studies the impact of process variations on the multi-Vth/Vddtechnique at the behavioral synthesis level. A multi-Vth/Vddresource library is characterized for delay and power variations at different voltage combinations. Meanwhile, device sizing is performed on the resources in the library to mitigate the impact of variation, and to enlarge the design space for better quality of the design choice. A parametric yield-driven resource binding algorithm is then proposed, which uses the characterized power and delay distributions and efficiently maximizes power yield under a timing yield constraint. During the resource binding process, voltage level converters are inserted between resources when required. Experimental results show that significant power reduction can be achieved with the proposed variation-aware framework, compared with traditional worstcase based deterministic approaches.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,General Computer Science,Signal Processing

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