VLSI Architectures of Approximate Arithmetic Units Applied to Parallel Sensors Calibration

Abstract

Approximate computing maximizes area and energy savings for a trade-off between quality and efficiency. Approximate arithmetic operators have emerged as an efficient alternative to design low-power VLSI circuits. This paper investigates the design of approximate arithmetic operator units used in the calibration procedure for radio astronomy light sensors — the so-called StEFCal (statistically efficient and fast calibration) method. The StEFCal algorithm comprises arithmetic operations like a divider, square-accumulate (SAC), and multiply-accumulate (MAC) units. The StEFCal circuit of this work explores the following arithmetic operators: i) two approximate squarer units from the literature, i.e., radix-4 (AxRSU) and SquASH, ii) two approximate iterative-based Newton-Raphson (NR) and Goldschmidt (GLD) dividers, iii) one approximate parallel prefix adder (AxPPA), and iv) a new approximate radix-4 multiplier (AxRMU), proposed in this work, explored in the StEFCal multiply-accumulate circuit design. The AxRSU utilizes the parameters <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K1$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K2$ </tex-math></inline-formula> to represent the number of exact encoders for squarer- and conventional-partial products, respectively, subsequently replaced with approximate encoders. The same principle applies to AxRMU, where the parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> indicates the number of exact encoders for conventional-partial products, subsequently exchanged with approximate encoders. We demonstrate the efficiency of StEFCal using the approximate arithmetic operators from the Pareto-optimal front that expresses the area- and power-quality trade-off. The results show that using the AxRSU with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K1=4$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K2=6$ </tex-math></inline-formula> , AxRMU, and AxPPA with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K=16$ </tex-math></inline-formula> and NR with one iteration has an MSE equal to 89.98dB and offers up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$158\times $ </tex-math></inline-formula> energy-savings compared to the exact StEFCal, and up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$25\times $ </tex-math></inline-formula> more energy-savings and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.33\times $ </tex-math></inline-formula> area-savings compared with our previous work, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$440\times $ </tex-math></inline-formula> energy-savings compared to the accurate state-of-the-art, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$258\times $ </tex-math></inline-formula> compared with the approximate state-of-the-art.