Shared Recurrence Floating-Point Divide/Sqrt and Integer Divide/Remainder With Early Termination

Division, square root, and remainder are fundamental operations required by most computer systems. Floating-point and integer operations are commonly performed on separate datapaths. This paper presents the first detailed implementation of a shared recurrence unit that supports floating-point division/square root and integer division/remainder. It supports early termination and shares the normalization shifter needed for integer and subnormal inputs. Synthesis results show that shared double-precision dividers producing at least 4 bits per cycle are 9 - 18% smaller and 3 - 16% faster than separate integer and floating-point units.

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Publication Details

Journal
IEEE Transactions on Computers
Published
2024-11-18
DOI
https://doi.org/10.1109/tc.2024.3500380
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
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Shared Recurrence Floating-Point Divide/Sqrt and Integer Divide/Remainder With Early Termination

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Shared Recurrence Floating-Point Divide/Sqrt and Integer Divide/Remainder With Early Termination

James E. Stine, Katherine Parry, Kevin Kim, David L. Harris, Cedar Turek, Robert C. Thompson, Alessandro Maiuolo
article en

Abstract

Division, square root, and remainder are fundamental operations required by most computer systems. Floating-point and integer operations are commonly performed on separate datapaths. This paper presents the first detailed implementation of a shared recurrence unit that supports floating-point division/square root and integer division/remainder. It supports early termination and shares the normalization shifter needed for integer and subnormal inputs. Synthesis results show that shared double-precision dividers producing at least 4 bits per cycle are 9 - 18% smaller and 3 - 16% faster than separate integer and floating-point units.

IEEE Transactions on ComputersVol. 74(2)
Oklahoma State University (US), Harvey Mudd College (US), Oklahoma State University Oklahoma City (US), Carnegie Mellon University (US)
Openalex Percentile: Top 81%
Cryptography and Data Security
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