NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System

Qingcai JiangBuxin TuXiaoyu HaoJunshi ChenHong An

体系结构与近数据计算方向论文：NDFT: Accelerating Density Functional Theory Calculations via Hardware/S

◫预览 PDFPreview PDF ↓下载 PDFDownload PDF ↗在线页面Official page ◇DOI

内容导读Reading note

分类与摘要Category & abstract

从处理器、指令、内存或近数据计算角度优化科学工作负载。

Evidence note

cai Jiang 1∗, Buxin Tu 1∗, Xiaoyu Hao 1, Junshi Chen 1,2 and Hong An 1,2,† 1School of Computer Science and Technology, University of Science and Technology of China, Hefei, China 2Laoshan Laboratory, Qingdao, China Abstract—Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical systems. Pre- vious works have atte || cai Jiang 1∗, Buxin Tu 1∗, Xiaoyu Hao 1, Junshi Chen 1,2 and Hong An 1,2,† 1School of Computer Science and Technology, University of Science and Technology of China, Hefei, China 2Laoshan Laboratory, Qingdao, China Abstract—Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical systems. Pre- vious work || ported by Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB0500102). The computing resources are financially sup- ported by Laoshan Laboratory (LSKJ202300305). REFERENCES [1] S. Aga, N. Jayasena, and M. Ignatowski. Co-ml: a case for co llaborative ml acceleration using near-data processing. In Proceedings of the International Symposium on Memory Systems , pages 506–517, 2019 || ported by Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB0500102). The computing resources are financially sup- ported by Laoshan Laboratory (LSKJ202300305). REFERENCES [1] S. Aga, N. Jayasena, and M. Ignatowski. Co-ml: a case for co llaborative ml acceleration using near-data processing. In Proceedings of the International Symposium on Memory Systems , pages 506–

Metadata

完整论文信息Full record

title: NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System
title_zh: 待补充
abstract: 待补充
abstract_zh: 待补充
keywords: Architecture, DFT, 学位认定 A, CCF A
year: 2025
published_date: 待补充
online_date: 待补充
paper_type: Conference
publication_status: Published
volume: 待补充
issue: 待补充
pages: 待补充
article_number: 待补充
publisher: IEEE
doi: 10.1109/dac63849.2025.11133299
research_area: 体系结构与近数据计算
tags: Architecture, DFT, 学位认定 A, CCF A
category: 体系结构与近数据计算
summary: 从处理器、指令、内存或近数据计算角度优化科学工作负载。
authors: Qingcai Jiang, Buxin Tu, Xiaoyu Hao, Junshi Chen, Hong An
corresponding_authors: 待补充
affiliations: 崂山实验室, 待补充
funding: 崂山实验室项目

Research area

体系结构与近数据计算

Citation

Qingcai Jiang*, Buxin Tu*, Xiaoyu Hao, Junshi Chen, Hong An， NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System, in the Proceeding of the 62th ACM/IEEE Design Automation Conference (DAC'2025) （CCFA）

BibTeX

@article{acsa2025_21,
  title = {NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System},
  year = {2025},
  doi = {10.1109/dac63849.2025.11133299}
}