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Customized Precision for Discontinuous Galerkin Methods using Adaptive Spectral Block Floating Point

Title data

Sundriyal, Shivam ; Büttner, Markus ; Kenter, Tobias ; Aizinger, Vadym:
Customized Precision for Discontinuous Galerkin Methods using Adaptive Spectral Block Floating Point.
In: Proceedings of the Platform for Advanced Scientific Computing Conference. - New York, NY : Association for Computing Machinery , 2026 . - 22
ISBN 979-8-4007-2734-4
DOI: https://doi.org/10.1145/3815572.3815758

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
Performance-optimiertes Co-Design von Ozeanmodellierungssoftware auf FPGAs
502500606

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

Discontinuous Galerkin (DG) methods offer high-order accuracy and geometric flexibility, but come with significant memory demands for storing degrees of freedom of the numerical solution -this remains a major performance bottleneck for large-scale simulations. Building on prior work introducing a 64-bit Adaptive Spectral Block Floating Point (ASBFP) format for modal 1D DG discretizations, we develop a more general framework that supports arbitrary polynomial order and arbitrary bit-width allocations. The extended ASBFP design constructs shared- and biased-exponent structures tailored to exploit the spectral decay of solution coefficients in modal DG bases, enabling fine-grained control over precision while providing both reduced- and extended-precision representations within a unified encoding model. Numerical tests in one dimension show that the generalized ASBFP format maintains the expected accuracy and convergence behaviour while substantially reducing the memory footprint across a wide range of DG orders.
We further extend the ASBFP methodology to multi-dimensional DG discretization based on tensor-product polynomial spaces. By identifying patterns in the decay of modal coefficients for multidimensional tensor-product bases and encoding hierarchical exponent offsets accordingly, this tensor-product-aware scheme enables more aggressive compression while maintaining numerical fidelity comparable to FP64 baselines. Together, these developments provide a flexible family of degree-aware spectral block floating-point formats for high-order DG methods in one and multiple dimensions.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Scientific Computing
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Scientific Computing > Chair Scientific Computing - Univ.-Prof. Dr. Mario Bebendorf
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Numerics of Partial Differential Equations
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Numerics of Partial Differential Equations > Chair Numerics of Partial Differential Equations - Univ.-Prof. Dr. Vadym Aizinger
Research Institutions > Central research institutes > Bayreuth Research Center for Modeling and Simulation - MODUS
Research Institutions > Central research institutes > Forschungszentrum für Wissenschaftliches Rechnen an der Universität Bayreuth - HPC-Forschungszentrum
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
500 Science > 510 Mathematics
Date Deposited: 01 Jul 2026 05:50
Last Modified: 01 Jul 2026 05:50
URI: https://eref.uni-bayreuth.de/id/eprint/98928