How Numerical Errors Scale with Hardware

In this short technical note, we outline how to bound numerical errors with respect to computational resources. We consider algorithms with known complexity estimates that can be executed in parallel and combine these estimates with parallelization laws. We suppose that the proposed approach generalizes beyond the presented examples and argue that it provides a straightforward and fair framework for comparing algorithms, hardware systems, and software implementations. This is achieved by imposing identical resource or energy budgets on each configuration, and comparing the resulting numerical error evaluations.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-26
DOI
https://doi.org/10.48550/arxiv.2610.35413
Primary Topic
Parallel Computing and Optimization Techniques
Type
preprint
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preprint

How Numerical Errors Scale with Hardware

Niklas Baumgarten
arXiv (Cornell University)
Parallel Computing and Optimization Techniques
preprint

How Numerical Errors Scale with Hardware

Niklas Baumgarten
preprint en

Abstract

In this short technical note, we outline how to bound numerical errors with respect to computational resources. We consider algorithms with known complexity estimates that can be executed in parallel and combine these estimates with parallelization laws. We suppose that the proposed approach generalizes beyond the presented examples and argue that it provides a straightforward and fair framework for comparing algorithms, hardware systems, and software implementations. This is achieved by imposing identical resource or energy budgets on each configuration, and comparing the resulting numerical error evaluations.

arXiv (Cornell University)
Parallel Computing and Optimization Techniques
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How Numerical Errors Scale with Hardware — Niklas Baumgarten · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS