Zhao Zhang

60 papers A 16B 3C 3Misc 1Journal 26Unranked 11
YearRankTypeTitle / Venue / Authors
2025 B conf
COMPSO: Optimizing Gradient Compression for Distributed Training with Second-Order Optimizers.
PPoPP
Baixi Sun, Weijin Liu, J. Gregory Pauloski, Jiannan Tian, Jinda Jia, Daoce Wang, Boyuan Zhang, Mingkai Zheng, Sheng Di, Sian Jin, Zhao Zhang, Xiaodong Yu, Kamil A. Iskra, Pete Beckman, Guangming Tan, Dingwen Tao
2025 A conf
Demystifying the Resilience of Large Language Model Inference: An End-to-End Perspective.
SC
Yu Sun, Zachary Coalson, Shiyang Chen, Hang Liu, Zhao Zhang, Sanghyun Hong, Bo Fang, Lishan Yang
2025 — conf
Diamond: Harnessing GPU Resources for Scientific Deep Learning.
eScience
Haotian Xie, Rohan Marwaha, Minu Mathew, Song Bian, Gengcong Yang, Minghao Yan, Yadu N. Babuji, Owen Price, Yinzhi Wang, Volodymyr V. Kindratenko, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang
2025 J jnl
Efficient Fine-Grained GPU Performance Modeling for Distributed Deep Learning of LLM.
CoRR
Biyao Zhang, Mingkai Zheng, Debargha Ganguly, Xuecen Zhang, Vikash Singh, Vipin Chaudhary, Zhao Zhang
2025 Misc conf
Efficient Fine-Grained Gpu Performance Modeling for Distributed Deep Learning of Llm.
HiPC
Biyao Zhang, Mingkai Zheng, Debargha Ganguly, Xuecen Zhang, Vikash Singh, Vipin Chaudhary, Zhao Zhang
2025 A conf
FT2: First-Token-Inspired Online Fault Tolerance on Critical Layers for Generative Large Language Models.
HPDC
Yu Sun, Zhu Zhu, Cherish Mulpuru, Roberto Gioiosa, Zhao Zhang, Bo Fang, Lishan Yang
2025 — conf
Radius: Range-based Gradient Sparsity for Large Foundation Model Pre-training.
MLSys
Mingkai Zheng, Zhao Zhang
2025 J jnl
Understanding the Landscape of Ampere GPU Memory Errors.
CoRR
Zhu Zhu, Yu Sun, Dhatri Parakal, Bo Fang, Steven Farrell, Gregory H. Bauer, Brett M. Bode, Ian T. Foster, Michael E. Papka, William Gropp, Zhao Zhang, Lishan Yang
2023 A conf
Fine-grained Policy-driven I/O Sharing for Burst Buffers.
SC
Ed Karrels, Lei Huang, Yuhong Kan, Ishank Arora, Yinzhi Wang, Daniel S. Katz, William Gropp, Zhao Zhang
2023 J jnl
Fine-grained Policy-driven I/O Sharing for Burst Buffers.
CoRR
Ed Karrels, Lei Huang, Yuhong Kan, Ishank Arora, Yinzhi Wang, Daniel S. Katz, William D. Gropp, Zhao Zhang
2023 A conf
Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning.
SC
Qiyang Ding, Pengfei Zheng, Shreyas Kudari, Shivaram Venkataraman, Zhao Zhang
2023 J jnl
Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning.
CoRR
Qiyang Ding, Pengfei Zheng, Shreyas Kudari, Shivaram Venkataraman, Zhao Zhang
2022 J jnl
Deep Neural Network Training With Distributed K-FAC.
IEEE Trans. Parallel Distributed Syst.
J. Gregory Pauloski, Lei Huang, Weijia Xu, Kyle Chard, Ian T. Foster, Zhao Zhang
2021 C conf
Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights.
CLUSTER
Bo Fang, Daoce Wang, Sian Jin, Quincey Koziol, Zhao Zhang, Qiang Guan, Suren Byna, Sriram Krishnamoorthy, Dingwen Tao
2021 J jnl
Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights.
CoRR
Bo Fang, Daoce Wang, Sian Jin, Quincey Koziol, Zhao Zhang, Qiang Guan, Suren Byna, Sriram Krishnamoorthy, Dingwen Tao
2021 J jnl
KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks.
CoRR
J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang
2021 A conf
KAISA: an adaptive second-order optimizer framework for deep neural networks.
SC
J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang
2021 C conf
Optimizing GPU-Enhanced HPC System and Cloud Procurements for Scientific Workloads.
ISC
Richard Todd Evans, Matthew Cawood, Stephen Lien Harrell, Lei Huang, Si Liu, Chun-Yaung Lu, Amit Ruhela, Yinzhi Wang, Zhao Zhang
2020 J jnl
Convolutional Neural Network Training with Distributed K-FAC.
CoRR
J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster
2020 A conf
Convolutional neural network training with distributed K-FAC.
SC
J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster
2020 A conf
Efficient I/O for Neural Network Training with Compressed Data.
IPDPS
Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster
2020 J jnl
Kira: Processing Astronomy Imagery Using Big Data Technology.
IEEE Trans. Big Data
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
2020 J jnl
The Limit of the Batch Size.
CoRR
Yang You, Yuhui Wang, Huan Zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh
2019 — conf
Aggregating Local Storage for Scalable Deep Learning I/O.
DLS@SC
Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster
2019 J jnl
Fast Deep Neural Network Training on Distributed Systems and Cloud TPUs.
IEEE Trans. Parallel Distributed Syst.
Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
2019 C conf
Quantifying the Impact of Memory Errors in Deep Learning.
CLUSTER
Zhao Zhang, Lei Huang, Ruizhu Huang, Weijia Xu, Daniel S. Katz
2018 A conf
BeeFlow: A Workflow Management System for In Situ Processing across HPC and Cloud Systems.
ICDCS
Jieyang Chen, Qiang Guan, Zhao Zhang, Xin Liang, Louis James Vernon, Allen McPherson, Li-Ta Lo, Patricia Grubel, Tim Randles, Zizhong Chen, James P. Ahrens
2018 J jnl
FanStore: Enabling Efficient and Scalable I/O for Distributed Deep Learning.
CoRR
Zhao Zhang, Lei Huang, Uri Manor, Linjing Fang, Gabriele Merlo, Craig Michoski, John Cazes, Niall Gaffney
2018 B conf
ImageNet Training in Minutes.
ICPP
Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
2017 J jnl
100-epoch ImageNet Training with AlexNet in 24 Minutes.
CoRR
Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel
2017 A conf
Diagnosing Machine Learning Pipelines with Fine-grained Lineage.
HPDC
Zhao Zhang, Evan Randall Sparks, Michael J. Franklin
2016 J jnl
A convergence of key-value storage systems from clouds to supercomputers.
Concurr. Comput. Pract. Exp.
Tonglin Li, Xiaobing Zhou, Ke Wang, Dongfang Zhao, Iman Sadooghi, Zhao Zhang, Ioan Raicu
2016 J jnl
Application Skeleton: Generating Synthetic Applications for Infrastructure Research.
J. Open Source Softw.
Zhao Zhang, Daniel S. Katz, André Merzky, Matteo Turilli, Shantenu Jha, Yadu Nand Babuji
2016 J jnl
Application skeletons: Construction and use in eScience.
Future Gener. Comput. Syst.
Daniel S. Katz, André Merzky, Zhao Zhang, Shantenu Jha
2016 A conf
Integrating Abstractions to Enhance the Execution of Distributed Applications.
IPDPS
Matteo Turilli, Feng Liu, Zhao Zhang, André Merzky, Michael Wilde, Jon B. Weissman, Daniel S. Katz, Shantenu Jha
2015 J jnl
Integrating Abstractions to Enhance the Execution of Distributed Applications.
CoRR
Matteo Turilli, Feng Liu, Zhao Zhang, André Merzky, Michael Wilde, Jon B. Weissman, Daniel S. Katz, Shantenu Jha
2015 — conf
Rethinking Data-Intensive Science Using Scalable Analytics Systems.
SIGMOD Conference
Frank Austin Nothaft, Matt Massie, Timothy Danford, Zhao Zhang, Uri Laserson, Carl Yeksigian, Jey Kottalam, Arun Ahuja, Jeff Hammerbacher, Michael D. Linderman, Michael J. Franklin, Anthony D. Joseph, David A. Patterson
2015 J jnl
Scientific Computing Meets Big Data Technology: An Astronomy Use Case.
CoRR
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
2015 — conf
Scientific computing meets big data technology: An astronomy use case.
IEEE BigData
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan Randall Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
2015 A conf
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox.
CIDR
Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan
2014 — conf
FusionFS: Toward supporting data-intensive scientific applications on extreme-scale high-performance computing systems.
IEEE BigData
Dongfang Zhao, Zhao Zhang, Xiaobing Zhou, Tonglin Li, Ke Wang, Dries Kimpe, Philip H. Carns, Robert B. Ross, Ioan Raicu
2014 J jnl
Special issue on eScience infrastructure and applications.
Future Gener. Comput. Syst.
Daniel S. Katz, Zhao Zhang
2014 J jnl
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox.
CoRR
Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan
2014 — conf
Using Application Skeletons to Improve eScience Infrastructure.
eScience
Zhao Zhang, Daniel S. Katz
2013 A conf
MTC envelope: defining the capability of large scale computers in the context of parallel scripting applications.
HPDC
Zhao Zhang, Daniel S. Katz, Michael Wilde, Justin M. Wozniak, Ian T. Foster
2013 A conf
Parallelizing the execution of sequential scripts.
SC
Zhao Zhang, Daniel S. Katz, Timothy G. Armstrong, Justin M. Wozniak, Ian T. Foster
2013 A conf
ZHT: A Light-Weight Reliable Persistent Dynamic Scalable Zero-Hop Distributed Hash Table.
IPDPS
Tonglin Li, Xiaobing Zhou, Kevin Brandstatter, Dongfang Zhao, Ke Wang, Anupam Rajendran, Zhao Zhang, Ioan Raicu
2012 B conf
A Workflow-Aware Storage System: An Opportunity Study.
CCGRID
Emalayan Vairavanathan, Samer Al-Kiswany, Lauro Beltrão Costa, Zhao Zhang, Daniel S. Katz, Michael Wilde, Matei Ripeanu
2012 A conf
Design and analysis of data management in scalable parallel scripting.
SC
Zhao Zhang, Daniel S. Katz, Justin M. Wozniak, Allan Espinosa, Ian T. Foster
2012 — conf
Job and data clustering for aggregate use of multiple production cyberinfrastructures.
DICT@HPDC
Ketan Maheshwari, Allan Espinosa, Daniel S. Katz, Michael Wilde, Zhao Zhang, Ian T. Foster, Scott Callaghan, Philip Maechling
2012 J jnl
Many-Task Computing and Blue Waters
CoRR
Daniel S. Katz, Timothy G. Armstrong, Zhao Zhang, Michael Wilde, Justin M. Wozniak
2011 — conf
AME: an anyscale many-task computing engine.
WORKS@SC
Zhao Zhang, Daniel S. Katz, Matei Ripeanu, Michael Wilde, Ian T. Foster
2010 J jnl
Middleware support for many-task computing.
Clust. Comput.
Ioan Raicu, Ian T. Foster, Mike Wilde, Zhao Zhang, Kamil Iskra, Peter H. Beckman, Yong Zhao, Alexander S. Szalay, Alok N. Choudhary, Philip Little, Christopher Moretti, Amitabh Chaudhary, Douglas Thain
2010 — conf
Scheduling many-task workloads on supercomputers: Dealing with trailing tasks.
MTAGS@SC
Timothy G. Armstrong, Zhao Zhang, Daniel S. Katz, Michael Wilde, Ian T. Foster
2009 J jnl
Design and Evaluation of a Collective IO Model for Loosely Coupled Petascale Programming
CoRR
Zhao Zhang, Allan Espinosa, Kamil Iskra, Ioan Raicu, Ian T. Foster, Michael Wilde
2009 J jnl
Parallel Scripting for Applications at the Petascale and Beyond.
Computer
Michael Wilde, Ian T. Foster, Kamil Iskra, Peter H. Beckman, Zhao Zhang, Allan Espinosa, Mihael Hategan, Ben Clifford, Ioan Raicu
2008 — conf
Design and evaluation of a collective IO model for loosely coupled petascale programming.
MTAGS@SC
Zhao Zhang, Allan Espinosa, Kamil Iskra, Ioan Raicu, Ian T. Foster, Michael Wilde
2008 J jnl
Enabling Loosely-Coupled Serial Job Execution on the IBM BlueGene/P Supercomputer and the SiCortex SC5832
CoRR
Ioan Raicu, Zhao Zhang, Michael Wilde, Ian T. Foster
2008 A conf
Toward loosely coupled programming on petascale systems.
SC
Ioan Raicu, Zhao Zhang, Michael Wilde, Ian T. Foster, Peter H. Beckman, Kamil Iskra, Ben Clifford
2008 J jnl
Towards Loosely-Coupled Programming on Petascale Systems
CoRR
Ioan Raicu, Zhao Zhang, Michael Wilde, Ian T. Foster, Peter H. Beckman, Kamil Iskra, Ben Clifford