Normalizing or not normalizing? An open question for floating-point arithmetic in embedded systems
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Abstract
Emerging embedded applications lack of a specific standard when they require floating-point arithmetic. In this situation they use the IEEE-754 standard or ad hoc variations of it. However, this standard was not designed for this purpose. This paper aims to open a debate to define a new extension of the standard to cover embedded applications. In this work, we only focus on the impact of not performing normalization. We show how eliminating the condition of normalized numbers, implementation costs can be dramatically reduced, at the expense of a moderate loss of accuracy. Several architectures to implement addition and multiplication for non-normalized numbers are proposed and analyzed. We show that a combined architecture (adder-multiplier) can halve the area and power consumption of its counterpart IEEE-754 architecture. This saving comes at the cost of reducing an average of about 10 dBs the Signal-to-Noise Ratio for the tested algorithms. We think these results should encourage researchers to perform further investigation in this issue.
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S. Gonzalez-Navarro and J. Hormigo, "Normalizing or Not Normalizing? An Open Question for Floating-Point Arithmetic in Embedded Systems," 2017 IEEE 24th Symposium on Computer Arithmetic (ARITH), London, United Kingdom, 2017, pp. 188-195. doi: 10.1109/ARITH.2017.16









