ByteQC: GPU-Accelerated Quantum Chemistry Package for Large-Scale Systems
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arXiv
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| Auteurs principaux: | , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866916783507636224 |
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| author | Guo, Zhen Huang, Zigeng Chen, Qiaorui Shao, Jiang Liu, Guangcheng Pham, Hung Q. Huang, Yifei Cao, Changsu Chen, Ji Lv, Dingshun |
| author_facet | Guo, Zhen Huang, Zigeng Chen, Qiaorui Shao, Jiang Liu, Guangcheng Pham, Hung Q. Huang, Yifei Cao, Changsu Chen, Ji Lv, Dingshun |
| contents | Applying quantum chemistry algorithms to large-scale systems requires substantial computational resources scaled with the system size and the desired accuracy. To address this, ByteQC, a fully-functional and efficient package for large-scale quantum chemistry simulations, has been open-sourced at https://github.com/bytedance/byteqc, leveraging recent advances in computational power and many-body algorithms.
Regarding computational power, several standard algorithms are efficiently implemented on modern GPUs, ranging from mean-field calculations (Hartree-Fock and density functional theory) to post-Hartree-Fock methods such as Møller-Plesset perturbation theory, random phase approximation, coupled cluster methods, and quantum Monte Carlo methods. For the algorithmic approach, we also employ a quantum embedding method, which significantly expands the tractable system size while preserving high accuracy at the gold-standard level.
All these features have been systematically benchmarked. For standalone algorithms, the benchmark results demonstrate up to a 60$\times$ speedup when compared to 100-core CPUs. Additionally, the tractable system sizes have been significantly expanded: 1,610 orbitals for coupled cluster with single and double excitations (1,380 orbitals with perturbative triple excitations), 11,040 orbitals for Møller-Plesset perturbation theory of second order, 37,120 orbitals for mean-field calculations under open boundary conditions, and over 100,000 orbitals for periodic boundary conditions. For the advanced quantum embedding feature, two representative examples are demonstrated: the water cluster problem (2,752 orbitals) and a water monomer adsorbed on a boron nitride surface (3,929 orbitals), achieving the gold-standard accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_17963 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ByteQC: GPU-Accelerated Quantum Chemistry Package for Large-Scale Systems Guo, Zhen Huang, Zigeng Chen, Qiaorui Shao, Jiang Liu, Guangcheng Pham, Hung Q. Huang, Yifei Cao, Changsu Chen, Ji Lv, Dingshun Chemical Physics Computational Physics Quantum Physics Applying quantum chemistry algorithms to large-scale systems requires substantial computational resources scaled with the system size and the desired accuracy. To address this, ByteQC, a fully-functional and efficient package for large-scale quantum chemistry simulations, has been open-sourced at https://github.com/bytedance/byteqc, leveraging recent advances in computational power and many-body algorithms. Regarding computational power, several standard algorithms are efficiently implemented on modern GPUs, ranging from mean-field calculations (Hartree-Fock and density functional theory) to post-Hartree-Fock methods such as Møller-Plesset perturbation theory, random phase approximation, coupled cluster methods, and quantum Monte Carlo methods. For the algorithmic approach, we also employ a quantum embedding method, which significantly expands the tractable system size while preserving high accuracy at the gold-standard level. All these features have been systematically benchmarked. For standalone algorithms, the benchmark results demonstrate up to a 60$\times$ speedup when compared to 100-core CPUs. Additionally, the tractable system sizes have been significantly expanded: 1,610 orbitals for coupled cluster with single and double excitations (1,380 orbitals with perturbative triple excitations), 11,040 orbitals for Møller-Plesset perturbation theory of second order, 37,120 orbitals for mean-field calculations under open boundary conditions, and over 100,000 orbitals for periodic boundary conditions. For the advanced quantum embedding feature, two representative examples are demonstrated: the water cluster problem (2,752 orbitals) and a water monomer adsorbed on a boron nitride surface (3,929 orbitals), achieving the gold-standard accuracy. |
| title | ByteQC: GPU-Accelerated Quantum Chemistry Package for Large-Scale Systems |
| topic | Chemical Physics Computational Physics Quantum Physics |
| url | https://arxiv.org/abs/2502.17963 |