[2607.06881] Multiple Double Arithmetic on NVIDIA Tensor Cores

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arXiv:2607.06881 (cs)

[Submitted on 8 Jul 2026]

Title:Multiple Double Arithmetic on NVIDIA Tensor Cores

Authors:Howard Chen, Jan Verschelde<br>View a PDF of the paper titled Multiple Double Arithmetic on NVIDIA Tensor Cores, by Howard Chen and Jan Verschelde

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Abstract:A multiple double is an unevaluated sum of doubles. An NVIDIA tensor core is a specialized high performance compute core for matrix multiplication. The Ampere A100, released in 2020, introduced tensor cores capable of 64-bit floating-point arithmetic. Every multiple double arithmetical operation requires renormalization, which involves branching, for which tensor cores are unsuited.

To solve this problem caused by renormalization, we apply a solution similar to the Ozaki scheme [Ozaki et al, Numerical Algorithms, 2012]. Our software is available under the GPU GPL license on github.

Comments:<br>accepted for inclusion in the proceedings of ICMS 2026, the International Conference on Mathematical Software

Subjects:

Mathematical Software (cs.MS); Distributed, Parallel, and Cluster Computing (cs.DC); Numerical Analysis (math.NA)

Cite as:<br>arXiv:2607.06881 [cs.MS]

(or<br>arXiv:2607.06881v1 [cs.MS] for this version)

https://doi.org/10.48550/arXiv.2607.06881

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arXiv-issued DOI via DataCite (pending registration)

Submission history<br>From: Jan Verschelde [view email]<br>[v1]<br>Wed, 8 Jul 2026 00:44:25 UTC (11 KB)

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