Jingxiao Ma
ABSTRACT
Approximate computing is an emerging computing paradigm that offers improved power consumption by relaxing the requirement for full accuracy. Since the requirements for accuracy may vary according to specific real-world applications, one trend of approximate computing is to design quality-configurable circuits, which are able to switch at runtime among different accuracy modes with different power and delay. In this paper, we present a novel framework RUCA which aims to synthesize runtime configurable approximate circuits based on arbitrary input circuits. By decomposing the truth table, our approach aims to approximate and separate the input circuit into multiple configuration blocks which support different accuracy levels, including a corrector circuit to restore full accuracy. Power gating is used to activate different blocks, such that the approximate circuit is able to operate at different accuracy-power configurations. To improve the scalability of our algorithm, we also provide a design space exploration scheme with circuit partitioning. We evaluate our methodology on a comprehensive set of benchmarks. For 3-level designs, RUCA saves power consumption by 43.71% within 2% error and by 30.15% within 1% error on average.
- T. Alan, A. Gerstlauer, and J. Henkel. 2020. Runtime accuracy-configurable approximate hardware synthesis using logic gating and relaxation. In Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 1578--1581.Google Scholar
- T. Alan, A. Gerstlauer, and J. Henkel. 2021. Cross-layer approximate hardware synthesis for runtime configurable accuracy. IEEE Transactions on Very Large Scale Integration (VLSI) Systems 29, 6 (2021), 1231--1243.Google ScholarCross Ref
- S. Boroumand, C. S. Bouganis, and G. A. Constantinides. 2021. Learning boolean circuits from examples for approximate logic synthesis. In Proceedings of the 26th Asia and South Pacific Design Automation Conference. 524--529.Google Scholar
- J. Castro-Godinez, H. Barrantes-Garcia, M. Shafique, and J. Henkel. 2021. AxLS: A framework for approximate logic synthesis based on netlist transformations. IEEE Transactions on Circuits and Systems II: Express Briefs 68, 8 (2021), 2845--2849.Google ScholarCross Ref
- S. Hashemi, R. I. Bahar, and S. Reda. 2016. A low-power dynamic divider for approximate applications. In 2016 53nd ACM/EDAC/IEEE Design Automation Conference (DAC). IEEE, 1--6.Google Scholar
- S. Jain, S. Venkataramani, and A. Raghunathan. 2016. Approximation through logic isolation for the design of quality configurable circuits. In Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 612--617.Google Scholar
- J. Ma, S. Hashemi, and S. Reda. 2021. Approximate Logic Synthesis Using Boolean Matrix Factorization. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.Google Scholar
- P. Miettinen, T. Mielikäinen, A. Gionis, G. Das, and H. Mannila. 2008. The discrete basis problem. IEEE transactions on knowledge and data engineering 20, 10 (2008), 1348--1362.Google Scholar
- V. Mrazek, Z. Vasicek, and L. Sekanina. 2018. Design of quality-configurable approximate multipliers suitable for dynamic environment. In 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS). IEEE, 264--271.Google Scholar
- K. Nepal, Y. Li, R. I. Bahar, and S. Reda. 2014. ABACUS: A technique for automated behavioral synthesis of approximate computing circuits. In 2014 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 1--6.Google Scholar
- S. Reda and M. Shafique. 2019. Approximate Circuits. Springer.Google Scholar
- I. Scarabottolo, G. Ansaloni, G. A. Constantinides, L. Pozzi, and S. Reda. 2020. Approximate logic synthesis: A survey. Proc. IEEE 108, 12 (2020), 2195--2213.Google ScholarCross Ref
- S. Schlag, V. Henne, T. Heuer, H. Meyerhenke, P. Sanders, and C. Schulz. 2016. k-way Hypergraph Partitioning via n-Level Recursive Bisection. In 18th Workshop on Algorithm Engineering and Experiments. 53--67.Google Scholar
- S. Venkataramani, K. Roy, and A. Raghunathan. 2013. Substitute-and-simplify: A unified design paradigm for approximate and quality configurable circuits. In Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 1367--1372.Google Scholar
Index Terms
- RUCA: RUntime Configurable Approximate Circuits with Self-Correcting Capability
Recommendations
Design of approximate Booth multipliers based on error compensation
AbstractWith the rapid development of the Internet of Things, terminal equipment is greatly restricted in hardware resources and power supply. Therefore, there is an urgent need for new low-power computing units. Aiming at the problem of high ...
Highlights- A new structure of approximate Booth encoder is proposed, which produces positive errors.
Invited - Cross-layer approximate computing: from logic to architectures
DAC '16: Proceedings of the 53rd Annual Design Automation ConferenceWe present a survey of approximate techniques and discuss concepts for building power-/energy-efficient computing components reaching from approximate accelerators to arithmetic blocks (like adders and multipliers). We provide a systematical ...
Approximate Multiplier Architectures Through Partial Product Perforation: Power-Area Tradeoffs Analysis
GLSVLSI '15: Proceedings of the 25th edition on Great Lakes Symposium on VLSIApproximate computing has received significant attention as a promising strategy to decrease power consumption of inherently error-tolerant applications. Hardware approximation mainly targets arithmetic units, e.g. adders and multipliers. In this paper, ...
Comments