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Performance and Algorithms Research

Nan Ding

IMG 9629
Nan Ding
Research Scientist
Mobile: 510-598-8318

Nan Ding is a Research Scientist in the Performance and Algorithms group of the Computer Science Department at Lawrence Berkeley National LaboratoryHer research interests include high-performance computing, performance modeling and auto-tuning. Nan received her Ph.D. in computer science from Tsinghua University, Beijing, China in 2018.

Journal Articles

Nan Ding, Muaaz Awan, Samuel Williams, "Instruction Roofline: An insightful visual performance model for GPUs", CCPE, August 4, 2021, doi: 10.1002/cpe.6591

Nan Ding, Victor W. Lee, Wei Xue, Weimin Zheng, "APMT: an automatic hardware counter-based performance modeling tool for HPC applications", CCF Transactions on High Performance Computing, June 24, 2020,

Nan Ding, Shiming Xu, Zhenya Song, Baoquan Zhang, Jingmei Li, Zhigao Zheng, "Using Hardware Counters-based Performance Model to Diagnose Scaling Issues of HPC Applications", NCAA'18, April 25, 2018,

Nan Ding, WeiXue, Zhenya Song, Haohuan Fub, Shiming Xu, WeiminZhenga, "An automatic performance model-based scheduling tool for coupled climate system models", JPDC, January 31, 2018,

Conference Papers

Muaaz Gul Awan,Steven Hofmeyr,Rob Egan,Nan Ding,Aydin Buluc,Jack Deslippe,Leonid Oliker,Katherine Yelick, "Accelerating Large Scale de Novo Metagenome Assembly Using GPUs", The International Conference for High Performance Computing, Networking, Storage and Analysis ( SC21), November 16, 2021,

Nan Ding, Yang Liu, Samuel Williams, Xiaoye S. Li, "A Message-Driven, Multi-GPU Parallel Sparse Triangular Solver", SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21), July 19, 2021,

Alberto Zeni, Giulia Guidi, Marquita Ellis, Nan Ding, Marco D. Santambrogio, Steven Hofmeyr, Aydın Buluç, Leonid Oliker, Katherine Yelick, "LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment", 34th IEEE International Parallel and Distributed Processing Symposium (IPDPS20), 2020, doi: 10.1109/IPDPS47924.2020.00055

Nan Ding, Samuel Williams, Yang Liu, Xiaoye S. Li, "Leveraging One-Sided Communication for Sparse Triangular Solvers", 2020 SIAM Conference on Parallel Processing for Scientific Computing, February 14, 2020,

Nan Ding, Samuel Williams, "An Instruction Roofline Model for GPUs", Performance Modeling, Benchmarking, and Simulation (PMBS), BEST PAPER AWARD, November 18, 2019,

Haohuan Fu, Junfeng Liao, Nan Ding, Xiaohui Duan, Lin Gan,Yishuang Liang,Xinliang Wang,Jinzhe Yang,Yan Zheng,Weiguo Liu,Lanning Wang,Guangwen Yang, "Redesigning CAM-SE for peta-scale climate modeling performance and ultra-high resolution on Sunway TaihuLight (ACM Gordon Bell Prize Finalist)", SC'17, November 12, 2017,

Haohuan Fu, Junfeng Liao, Wei Xue, Lanning Wang, Dexun Chen, Long Gu, Jinxiu Xu, Nan Ding, Xinliang Wang, Conghui He, Shizhen Xu, Yishuang Liang, Jiarui Fang, Yuanchao Xu, Weijie Zheng, etc., "Refactoring and optimizing the community atmosphere model (CAM) on the sunway taihulight supercomputer", SC'16, November 13, 2016,

Nan Ding, Weu Xue, Xu Ji, Haoyu Xu, Zhenya Song, "CESMTuner: An Auto-Tuning Framework for the Community Earth System Model", HPCC'14, IEEE, August 20, 2014, doi: 10.1109/HPCC.2014.51

Book Chapters

Wei Xue, Xiaoge Xin, Jie Zhang, Wusheng Zhang, Haiping Wu, Zhenchun Huang, Tao Zhang, Huimin Li, Nan Ding, Huang Huang, "Development and Testing of a Multi-model Ensemble Coupling Framework", Book, (Springer, Singapore: January 1, 2016) Pages: 163-208


Nan Ding, Samuel Williams, An Instruction Roofline Model for GPUs, Performance Modeling, Benchmarking, and Simulation (PMBS), BEST PAPER AWARD, November 18, 2019,


Nan Ding, Samuel Williams, Sherry Li, Yang Liu, "Leveraging One-Sided Communication for Sparse Triangular Solvers", SciDAC19, July 18, 2019,

Samuel Williams, Charlene Yang, Khaled Ibrahim, Thorsten Kurth, Nan Ding, Jack Deslippe, Leonid Oliker, "Performance Analysis using the Roofline Model", SciDAC PI Meeting, July 2019,

Nan Ding, Victor W Lee, Wei Xue, Weimin Zheng, "Understanding Potential Performance Issues Using Resource-based Alongside Time Models", SC'18, November 13, 2018,