Author

X. Li

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Preprint Sep 2026

Mixed-Precision Computing for Scientific Discovery: Formats, Co-Design, and Responsible Approximation

Reduced and mixed precision have moved from a niche optimization to a central design axis in scientific computing and engineering, driven by energy constraints, heterogeneous accelerators, and the convergence of simulation and machine learning. This paper organizes the landscape around seven coupled themes---number for...

E. Agullo, H. Anzt, Daniel Bauer et al. · 0 citations

Open access Oct 2025

Efficient Tensor Completion Algorithms for Highly Oscillatory Operators

A novel reformulation of the butterfly structure as a compact tensor network is proposed, leading to speedups of orders of magnitude and significant accuracy improvements for large matrices compared to state‐of‐the‐art low‐rank matrix and QTT tensor completion algorithms.

Navjot Singh, Edgar Solomonik, X. Li et al. · Numerical Linear Algebra wit... · 0 citations

Open access Jul 2026

Efficient Tensor Completion Algorithms for Highly Oscillatory Operators

We address the problem of recovering highly oscillatory operators, represented as matrices with a fixed set of observed entries. Given that these matrices can be well compressed by butterfly matrix decomposition of levels requiring only degrees of freedom, we propose a novel reformulation of the butterfly structure a...

Navjot Singh, Edgar Solomonik, X. Li et al. · Numerical Linear Algebra wit... · 0 citations