Automatic Verification of Floating-Point Accumulation Networks

Fuente: arXiv
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Main Authors: Zhang, David K., Aiken, Alex
Format: Preprint
Published: 2025
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author Zhang, David K.
Aiken, Alex
author_facet Zhang, David K.
Aiken, Alex
contents Floating-point accumulation networks (FPANs) are key building blocks used in many floating-point algorithms, including compensated summation and double-double arithmetic. FPANs are notoriously difficult to analyze, and algorithms using FPANs are often published without rigorous correctness proofs. In fact, on at least one occasion, a published error bound for a widely used FPAN was later found to be incorrect. In this paper, we present an automatic procedure that produces computer-verified proofs of several FPAN correctness properties, including error bounds that are tight to the nearest bit. Our approach is underpinned by a novel floating-point abstraction that models the sign, exponent, and number of leading and trailing zeros and ones in the mantissa of each number flowing through an FPAN. We also present a new FPAN for double-double addition that is faster and more accurate than the previous best known algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2505_18791
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Automatic Verification of Floating-Point Accumulation Networks
Zhang, David K.
Aiken, Alex
Numerical Analysis
Logic in Computer Science
Floating-point accumulation networks (FPANs) are key building blocks used in many floating-point algorithms, including compensated summation and double-double arithmetic. FPANs are notoriously difficult to analyze, and algorithms using FPANs are often published without rigorous correctness proofs. In fact, on at least one occasion, a published error bound for a widely used FPAN was later found to be incorrect. In this paper, we present an automatic procedure that produces computer-verified proofs of several FPAN correctness properties, including error bounds that are tight to the nearest bit. Our approach is underpinned by a novel floating-point abstraction that models the sign, exponent, and number of leading and trailing zeros and ones in the mantissa of each number flowing through an FPAN. We also present a new FPAN for double-double addition that is faster and more accurate than the previous best known algorithm.
title Automatic Verification of Floating-Point Accumulation Networks
topic Numerical Analysis
Logic in Computer Science
url https://arxiv.org/abs/2505.18791