One polynomial approximation to produce correctly rounded results of an elementary function for multiple representations and rounding modes
Jay P. Lim, Santosh Nagarakatte
Abstract
Mainstream math libraries for floating point (FP) do not produce correctly rounded results for all inputs. In contrast, CR-LIBM and RLIBM provide correctly rounded implementations for a specific FP representation with one rounding mode. Using such libraries for a representation with a new rounding mode or with different precision will result in wrong results due to double rounding. This paper proposes a novel method to generate a single polynomial approximation that produces correctly rounded results for all inputs for multiple rounding modes and multiple precision configurations. To generate a correctly rounded library for n -bits, our key idea is to generate a polynomial approximation for a representation with n +2-bits using the round-to-odd mode. We prove that the resulting polynomial approximation will produce correctly rounded results for all five rounding modes in the standard and for multiple representations with k -bits such that | E | +1 < k ≤ n , where | E | is the number of exponent bits in the representation. Similar to our prior work in the RLIBM project, we approximate the correctly rounded result when we generate the library with n +2-bits using the round-to-odd mode. We also generate polynomial approximations by structuring it as a linear programming problem but propose enhancements to polynomial generation to handle the round-to-odd mode. Our prototype is the first 32-bit float library that produces correctly rounded results with all rounding modes in the IEEE standard for all inputs with a single polynomial approximation. It also produces correctly rounded results for any FP configuration ranging from 10-bits to 32-bits while also being faster than mainstream libraries.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext a01e1132-bae8-4c53-8cf6-84ef8026e847Cited by top-tier papers9
- Fast shadow execution for debugging numerical errors using error free transformationsSangeeta Chowdhary, Santosh NagarakatteOOPSLA 2022 · 13 citations
- Progressive polynomial approximations for fast correctly rounded math librariesMridul Aanjaneya, Jay P. Lim, Santosh NagarakattePLDI 2022 · 9 citations
- Implementation and Synthesis of Math Library FunctionsIan Briggs, Yash Lad, Pavel PanchekhaPOPL 2024 · 7 citations
- Numerical Fuzz: A Type System for Rounding Error AnalysisAriel E. Kellison, Justin HsuPLDI 2024 · 4 citations
- MiSo: A DSL for Robust and Efficient Solve and MInimize ProblemsFederico Sichetti, Enrico Puppo, Zizhou Huang, Marco Attene et al.SIGGRAPH 2025 · 1 citation
Builds on4
- Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating PointBita Darvish Rouhani, Daniel Lo, Ritchie Zhao, Ming Liu et al.NeurIPS 2020 · 153 citations
- Detecting floating-point errors via atomic conditionsDaming Zou, Muhan Zeng, Yingfei Xiong, Zhoulai Fu et al.POPL 2020 · 45 citations
- An approach to generate correctly rounded math libraries for new floating point variantsJay P. Lim, Mridul Aanjaneya, John L. Gustafson, Santosh NagarakattePOPL 2021 · 21 citations
- High performance correctly rounded math libraries for 32-bit floating point representationsJay P. Lim, Santosh NagarakattePLDI 2021 · 19 citations
Related papers
- Correctly Rounded Math Libraries without Worrying about the Application's Rounding ModeSehyeok Park, Justin Kim, Santosh NagarakattePLDI 2025 · 1 citation
- High-Performance Branch-Free Algorithms for Extended-Precision Floating-Point ArithmeticDavid Kai Zhang, Alex AikenSC 2025 · 3 citations
- Maximum Consensus Floating Point Solutions for Infeasible Low-Dimensional Linear Programs with Convex Hull as the Intermediate RepresentationMridul Aanjaneya, Santosh NagarakattePLDI 2024 · 1 citation
- FPVM: Towards a Floating Point Virtual MachinePeter A. Dinda, Nick Wanninger, Jiacheng Ma, Alex Bernat et al.HPDC 2022 · 4 citations
- Automatic Verification of Floating-Point Accumulation NetworksDavid Kai Zhang, Alex AikenCAV 2025 · 2 citations
