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Half-Unit-Biased (HUB) is an emerging format based on shifting the represented numbers by half Unit in the Last Place. This format simplifies two's complement and roundto-nearest operations by preventing any carry propagation. This saves power consumption, time and area. Taking into account that the IEEE floating-point standard uses an unbiased rounding as the default mode, this feature is also desirable for HUB approaches. In this paper, we study the unbiased rounding for HUB floating-point addition in both as standalone operation and within FMA. We show two different alternatives to eliminate the bias when rounding the sum results, either partially or totally. We also present an error analysis and the implementation results of the proposed architectures to help the designers to decide what their best option are.

In this work, we propose a new decimal redundant CORDIC algorithm to manage transcendental functions, using floatingpoint representation. The algorithms determine the direction of the elementary rotation using sign estimations. Unlike binary redundant CORDIC, repetition of iterations are not required to ensure convergence since novel decimal codes have been carefully selected with sufficient redundancy to prevent any repetition. The algorithms are mapped to a low-cost unit based on a decimal 3-2 carry-save adder which can also be used as a floating-point decimal division unit. Compared to current decimal floating-point units, the implementation of our algorithm involves minor modifications of the native hardware, while providing a huge set of elementary functions.

Floating point reproducibility is a property claimed by programmers and end users. Half-Unit-Biased (HUB) is a new representation format in which the round to nearest is carried out by truncation, preventing any carry propagation and saving time and area. In this paper we study the reproducible summation of HUB numbers by using a errorfree vector transformation technique, providing both a specific architecture and the usage of combined HUB/Standard floating point adders to achieve a reproducible result.

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