Presentation
Approx-T: Design Methodology for Approximate Multiplication Units via Taylor-expansion
DescriptionApproximate computing is emerging as a promising approach to devise energy-efficient IoT systems by exploiting the inherent error-tolerant nature of various applications. In this work, we present Approx-T, a novel design methodology that conducts an in-depth study on Approximate Multiplication Units (AMUs) via Taylor-expansion. This paper comprises three key contributions: (1) Pioneering the incorporation of Taylor's theorem into the design concept of approximate units. (2) Leverage the inherent symmetrical error distribution of Taylor series to conduct unbiased AMUs. (3) Present a runtime configurable error compensation architecture with low-complexity arithmetic operations. We implemented both approximate integer and floating multiplication arithmetic units and compared with the state-of-the-art approximations, experimental results show that Approx-T outperforms in all aspects including precision, area and power consumption. We also deployed AMUs on embedded FPGA for various edge computing tasks, Approx-T can achieve up to 5.7x energy efficiency in CNN application with negligible impact on accuracy.
Event Type
Work-in-Progress Poster
TimeTuesday, June 256:00pm - 7:00pm PDT
LocationLevel 2 Lobby
AI
Autonomous Systems
Cloud
Design
EDA
Embedded Systems
IP
Security