Toward loosely coupled programming on petascale systems. - Ioan Raicu; Zhao Zhang 007; Michael Wilde; Ian T. Foster; Peter H. Beckman; Kamil Iskra; Ben Clifford (SC, 2008)

Design and evaluation of a collective IO model for loosely coupled petascale programming. - Zhao Zhang 007; Allan Espinosa; Kamil Iskra; Ioan Raicu; Ian T. Foster; Michael Wilde (MTAGS@SC, 2008)

Enabling Loosely-Coupled Serial Job Execution on the IBM BlueGene/P Supercomputer and the SiCortex SC5832 - Ioan Raicu; Zhao Zhang 007; Michael Wilde; Ian T. Foster (CoRR, 2008)

Towards Loosely-Coupled Programming on Petascale Systems - Ioan Raicu; Zhao Zhang 007; Michael Wilde; Ian T. Foster; Peter H. Beckman; Kamil Iskra; Ben Clifford (CoRR, 2008)

Parallel Scripting for Applications at the Petascale and Beyond. - Michael Wilde; Ian T. Foster; Kamil Iskra; Peter H. Beckman; Zhao Zhang 007; Allan Espinosa; Mihael Hategan; Ben Clifford; Ioan Raicu (Computer, 2009)

Scheduling many-task workloads on supercomputers: Dealing with trailing tasks. - Timothy G. Armstrong; Zhao Zhang 007; Daniel S. Katz; Michael Wilde; Ian T. Foster (MTAGS@SC, 2010)

Middleware support for many-task computing. - Ioan Raicu; Ian T. Foster; Mike Wilde; Zhao Zhang 007; Kamil Iskra; Peter H. Beckman; Yong Zhao 009; Alexander S. Szalay; Alok N. Choudhary; Philip Little; Christopher Moretti; Amitabh Chaudhary; et al. (Clust. Comput., 2010)

AME: an anyscale many-task computing engine. - Zhao Zhang 007; Daniel S. Katz; Matei Ripeanu; Michael Wilde; Ian T. Foster (WORKS@SC, 2011)

A Workflow-Aware Storage System: An Opportunity Study. - Emalayan Vairavanathan; Samer Al-Kiswany; Lauro Beltrão Costa; Zhao Zhang 007; Daniel S. Katz; Michael Wilde; Matei Ripeanu (CCGRID, 2012)

Job and data clustering for aggregate use of multiple production cyberinfrastructures. - Ketan Maheshwari; Allan Espinosa; Daniel S. Katz; Michael Wilde; Zhao Zhang 007; Ian T. Foster; Scott Callaghan; Philip Maechling (DICT@HPDC, 2012)

Design and analysis of data management in scalable parallel scripting. - Zhao Zhang 007; Daniel S. Katz; Justin M. Wozniak; Allan Espinosa; Ian T. Foster (SC, 2012)

Many-Task Computing and Blue Waters - Daniel S. Katz; Timothy G. Armstrong; Zhao Zhang 007; Michael Wilde; Justin M. Wozniak (CoRR, 2012)

MTC envelope: defining the capability of large scale computers in the context of parallel scripting applications. - Zhao Zhang 007; Daniel S. Katz; Michael Wilde; Justin M. Wozniak; Ian T. Foster (HPDC, 2013)

ZHT: A Light-Weight Reliable Persistent Dynamic Scalable Zero-Hop Distributed Hash Table. - Tonglin Li; Xiaobing Zhou; Kevin Brandstatter; Dongfang Zhao 001; Ke Wang 012; Anupam Rajendran; Zhao Zhang 007; Ioan Raicu (IPDPS, 2013)

Parallelizing the execution of sequential scripts. - Zhao Zhang 007; Daniel S. Katz; Timothy G. Armstrong; Justin M. Wozniak; Ian T. Foster (SC, 2013)

FusionFS: Toward supporting data-intensive scientific applications on extreme-scale high-performance computing systems. - Dongfang Zhao 001; Zhao Zhang 007; Xiaobing Zhou; Tonglin Li; Ke Wang 012; Dries Kimpe; Philip H. Carns; Robert B. Ross; Ioan Raicu (IEEE BigData, 2014)

Using Application Skeletons to Improve eScience Infrastructure. - Zhao Zhang 007; Daniel S. Katz (eScience, 2014)

Special issue on eScience infrastructure and applications. - Daniel S. Katz; Zhao Zhang 007 (Future Gener. Comput. Syst., 2014)

Scientific computing meets big data technology: An astronomy use case. - Zhao Zhang 007; Kyle Barbary; Frank Austin Nothaft; Evan Randall Sparks; Oliver Zahn; Michael J. Franklin; David A. Patterson 001; Saul Perlmutter (IEEE BigData, 2015)

The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox. - Daniel Crankshaw; Peter Bailis; Joseph E. Gonzalez; Haoyuan Li 001; Zhao Zhang 007; Michael J. Franklin; Ali Ghodsi 002; Michael I. Jordan (CIDR, 2015)

Rethinking Data-Intensive Science Using Scalable Analytics Systems. - Frank Austin Nothaft; Matt Massie; Timothy Danford; Zhao Zhang 007; Uri Laserson; Carl Yeksigian; Jey Kottalam; Arun Ahuja; Jeff Hammerbacher; Michael D. Linderman; Michael J. Franklin; Anthony D. Joseph; et al. (SIGMOD Conference, 2015)

Integrating Abstractions to Enhance the Execution of Distributed Applications. - Matteo Turilli; Feng Liu; Zhao Zhang 007; André Merzky; Michael Wilde; Jon B. Weissman; Daniel S. Katz; Shantenu Jha (IPDPS, 2016)

A convergence of key-value storage systems from clouds to supercomputers. - Tonglin Li; Xiaobing Zhou; Ke Wang 012; Dongfang Zhao 001; Iman Sadooghi; Zhao Zhang 007; Ioan Raicu (Concurr. Comput. Pract. Exp., 2016)

Application skeletons: Construction and use in eScience. - Daniel S. Katz; André Merzky; Zhao Zhang 007; Shantenu Jha (Future Gener. Comput. Syst., 2016)

Application Skeleton: Generating Synthetic Applications for Infrastructure Research. - Zhao Zhang 007; Daniel S. Katz; André Merzky; Matteo Turilli; Shantenu Jha; Yadu Nand Babuji (J. Open Source Softw., 2016)

Diagnosing Machine Learning Pipelines with Fine-grained Lineage. - Zhao Zhang 007; Evan Randall Sparks; Michael J. Franklin (HPDC, 2017)

100-epoch ImageNet Training with AlexNet in 24 Minutes. - Yang You 001; Zhao Zhang 007; Cho-Jui Hsieh; James Demmel (CoRR, 2017)

BeeFlow: A Workflow Management System for In Situ Processing across HPC and Cloud Systems. - Jieyang Chen; Qiang Guan; Zhao Zhang 007; Xin Liang 001; Louis James Vernon; Allen McPherson; Li-Ta Lo; Patricia Grubel; Tim Randles; Zizhong Chen; James P. Ahrens (ICDCS, 2018)

ImageNet Training in Minutes. - Yang You 001; Zhao Zhang 007; Cho-Jui Hsieh; James Demmel; Kurt Keutzer (ICPP, 2018)

FanStore: Enabling Efficient and Scalable I/O for Distributed Deep Learning. - Zhao Zhang 007; Lei Huang 019; Uri Manor; Linjing Fang; Gabriele Merlo; Craig Michoski; John Cazes; Niall Gaffney (CoRR, 2018)

Quantifying the Impact of Memory Errors in Deep Learning. - Zhao Zhang 007; Lei Huang 019; Ruizhu Huang; Weijia Xu; Daniel S. Katz (CLUSTER, 2019)

Aggregating Local Storage for Scalable Deep Learning I/O. - Zhao Zhang 007; Lei Huang 019; J. Gregory Pauloski; Ian T. Foster (DLS@SC, 2019)

Fast Deep Neural Network Training on Distributed Systems and Cloud TPUs. - Yang You 001; Zhao Zhang 007; Cho-Jui Hsieh; James Demmel; Kurt Keutzer (IEEE Trans. Parallel Distributed Syst., 2019)

Efficient I/O for Neural Network Training with Compressed Data. - Zhao Zhang 007; Lei Huang 019; J. Gregory Pauloski; Ian T. Foster (IPDPS, 2020)

Convolutional neural network training with distributed K-FAC. - J. Gregory Pauloski; Zhao Zhang 007; Lei Huang 019; Weijia Xu; Ian T. Foster (SC, 2020)

The Limit of the Batch Size. - Yang You 001; Yuhui Wang; Huan Zhang 001; Zhao Zhang 007; James Demmel; Cho-Jui Hsieh (CoRR, 2020)

Kira: Processing Astronomy Imagery Using Big Data Technology. - Zhao Zhang 007; Kyle Barbary; Frank Austin Nothaft; Evan Randall Sparks; Oliver Zahn; Michael J. Franklin; David A. Patterson 001; Saul Perlmutter (IEEE Trans. Big Data, 2020)

Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights. - Bo Fang 002; Daoce Wang; Sian Jin; Quincey Koziol; Zhao Zhang 007; Qiang Guan; Suren Byna; Sriram Krishnamoorthy; Dingwen Tao (CLUSTER, 2021)

KAISA: an adaptive second-order optimizer framework for deep neural networks. - J. Gregory Pauloski; Qi Huang; Lei Huang 019; Shivaram Venkataraman; Kyle Chard; Ian T. Foster; Zhao Zhang 007 (SC, 2021)

Optimizing GPU-Enhanced HPC System and Cloud Procurements for Scientific Workloads. - Richard Todd Evans; Matthew Cawood; Stephen Lien Harrell; Lei Huang 019; Si Liu; Chun-Yaung Lu; Amit Ruhela; Yinzhi Wang; Zhao Zhang 007 (ISC, 2021)

Deep Neural Network Training With Distributed K-FAC. - J. Gregory Pauloski; Lei Huang 019; Weijia Xu; Kyle Chard; Ian T. Foster; Zhao Zhang 007 (IEEE Trans. Parallel Distributed Syst., 2022)

Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning. - Qiyang Ding; Pengfei Zheng; Shreyas Kudari; Shivaram Venkataraman; Zhao Zhang 007 (SC, 2023)

Fine-grained Policy-driven I/O Sharing for Burst Buffers. - Ed Karrels; Lei Huang 019; Yuhong Kan; Ishank Arora; Yinzhi Wang; Daniel S. Katz; William Gropp; Zhao Zhang 007 (SC, 2023)

COMPSO: Optimizing Gradient Compression for Distributed Training with Second-Order Optimizers. - Baixi Sun; Weijin Liu; J. Gregory Pauloski; Jiannan Tian; Jinda Jia; Daoce Wang; Boyuan Zhang 002; Mingkai Zheng; Sheng Di; Sian Jin; Zhao Zhang 007; Xiaodong Yu 001; et al. (PPoPP, 2025)

Understanding the Landscape of Ampere GPU Memory Errors. - Zhu Zhu; Yu Sun; Dhatri Parakal; Bo Fang 002; Steven Farrell; Gregory H. Bauer; Brett M. Bode; Ian T. Foster; Michael E. Papka; William Gropp; Zhao Zhang 007; Lishan Yang (CoRR, 2025)