GPU acceleration of plane-wave density functional theory calculations in Abinit
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866911724081250304 |
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| author | Lygatsika, Ioanna-Maria Sarraute, Marc Baguet, Lucas Kestener, Pierre Torrent, Marc |
| author_facet | Lygatsika, Ioanna-Maria Sarraute, Marc Baguet, Lucas Kestener, Pierre Torrent, Marc |
| contents | We report on the GPU port of the Abinit high-performance simulation code for plane-wave DFT calculations. Large-scale electronic structure calculations require computing the electronic wave function by solving the Kohn-Sham equations discretized over a large number of plane waves. Porting such calculations to GPU nodes relies not only on extensive usage of vendor libraries from a development perspective, but also on algorithmic revisions of the iterative diagonalization procedure in the resolution of the Kohn-Sham equations to identify GPU-efficient mathematical operations (linear algebra, FFTs) applied to the wave function distributed in memory. The present contribution discusses the Abinit implementation on multi-GPU architectures, providing detailed performance results for heterogeneous CPU-GPU nodes versus CPU nodes. Particular attention is given to comparing two diagonalization algorithms -- Locally Optimal Block Preconditioned Conjugate Gradient and Chebyshev polynomial filtering -- in terms of GPU efficiency. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2604_11139 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | GPU acceleration of plane-wave density functional theory calculations in Abinit Lygatsika, Ioanna-Maria Sarraute, Marc Baguet, Lucas Kestener, Pierre Torrent, Marc Materials Science We report on the GPU port of the Abinit high-performance simulation code for plane-wave DFT calculations. Large-scale electronic structure calculations require computing the electronic wave function by solving the Kohn-Sham equations discretized over a large number of plane waves. Porting such calculations to GPU nodes relies not only on extensive usage of vendor libraries from a development perspective, but also on algorithmic revisions of the iterative diagonalization procedure in the resolution of the Kohn-Sham equations to identify GPU-efficient mathematical operations (linear algebra, FFTs) applied to the wave function distributed in memory. The present contribution discusses the Abinit implementation on multi-GPU architectures, providing detailed performance results for heterogeneous CPU-GPU nodes versus CPU nodes. Particular attention is given to comparing two diagonalization algorithms -- Locally Optimal Block Preconditioned Conjugate Gradient and Chebyshev polynomial filtering -- in terms of GPU efficiency. |
| title | GPU acceleration of plane-wave density functional theory calculations in Abinit |
| topic | Materials Science |
| url | https://arxiv.org/abs/2604.11139 |