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Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications
- Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications
- Narayanamoorthy, Srinivasan; Moghaddam, Hadi Asghari; Liu, Zhenhong; Park, Taejoon; Kim, Nam Sung
- DGIST Authors
- Park, Taejoon
- Issue Date
- IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 23(6), 1180-1184
- Article Type
- Accuracy of Classifications; Approximation; Computational Accuracy; Computational Error; Digital Devices; Digital Signal Processing (DSP); Energy Efficiency; Energy Utilization; Errors; Fixed Point Arithmetic; Matrix Multiplication; Multiplication; Multiplier Architecture; Signal Processing
- The need to support various digital signal processing (DSP) and classification applications on energy-constrained devices has steadily grown. Such applications often extensively perform matrix multiplications using fixed-point arithmetic while exhibiting tolerance for some computational errors. Hence, improving the energy efficiency of multiplications is critical. In this brief, we propose multiplier architectures that can tradeoff computational accuracy with energy consumption at design time. Compared with a precise multiplier, the proposed multiplier can consume 58% less energy/op with average computational error of ∼ 1 %. Finally, we demonstrate that such a small computational error does not notably impact the quality of DSP and the accuracy of classification applications. © 1993-2012 IEEE.
- Institute of Electrical and Electronics Engineers Inc.
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