Theoretical Analysis and Optimization of Peak Memory Usage in PyPWDFT for Heterogeneous GPU High-Performance Computing

Jun Gao, Wenxin Peng, Bingkun Hou, Jinlong Yang, Wei Hu

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DOI: 10.1021/acs.jctc.6c01120
Published: 2026-09-10
Container: Journal of Chemical Theory and Computation
Publisher: American Chemical Society (ACS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jctc.6c01120,
  title = {Theoretical Analysis
and Optimization of Peak Memory
Usage in PyPWDFT for Heterogeneous GPU High-Performance Computing},
  author = {Jun Gao and Wenxin Peng and Bingkun Hou and Jinlong Yang and Wei Hu},
  year = {2026},
  journal = {Journal of Chemical Theory
and Computation},
  doi = {10.1021/acs.jctc.6c01120},
  url = {https://doi.org/10.1021/acs.jctc.6c01120}
}

RIS

TY  - JOUR
TI  - Theoretical Analysis
and Optimization of Peak Memory
Usage in PyPWDFT for Heterogeneous GPU High-Performance Computing
AU  - Jun Gao
AU  - Wenxin Peng
AU  - Bingkun Hou
AU  - Jinlong Yang
AU  - Wei Hu
PY  - 2026
JO  - Journal of Chemical Theory
and Computation
DO  - 10.1021/acs.jctc.6c01120
UR  - https://doi.org/10.1021/acs.jctc.6c01120
ER  -

APA

Gao, J., Peng, W., Hou, B., Yang, J., & Hu, W. (2026). Theoretical Analysis and Optimization of Peak Memory Usage in PyPWDFT for Heterogeneous GPU High-Performance Computing. Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.6c01120

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crossref · retrieved 2026-11-07T10:47:35.403Z