Zhao Zhang

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 27

Top Topics

Neural Network Training

Training Algorithm

Top Venues

Future Gener. Comput. Syst.

Publications

Qiyang Ding, Pengfei Zheng, Shreyas Kudari, Shivaram Venkataraman, Zhao Zhang
Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning. SC (2023)
Qiyang Ding, Pengfei Zheng, Shreyas Kudari, Shivaram Venkataraman, Zhao Zhang
Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning. CoRR (2023)
Ed Karrels, Lei Huang, Yuhong Kan, Ishank Arora, Yinzhi Wang, Daniel S. Katz, William Gropp, Zhao Zhang
Fine-grained Policy-driven I/O Sharing for Burst Buffers. SC (2023)
Ed Karrels, Lei Huang, Yuhong Kan, Ishank Arora, Yinzhi Wang, Daniel S. Katz, William D. Gropp, Zhao Zhang
Fine-grained Policy-driven I/O Sharing for Burst Buffers. CoRR (2023)
J. Gregory Pauloski, Lei Huang, Weijia Xu, Kyle Chard, Ian T. Foster, Zhao Zhang
Deep Neural Network Training With Distributed K-FAC. IEEE Trans. Parallel Distributed Syst. 33 (12) (2022)
J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang
KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks. CoRR (2021)
Richard Todd Evans, Matthew Cawood, Stephen Lien Harrell, Lei Huang, Si Liu, Chun-Yaung Lu, Amit Ruhela, Yinzhi Wang, Zhao Zhang
Optimizing GPU-Enhanced HPC System and Cloud Procurements for Scientific Workloads. ISC (2021)
Bo Fang, Daoce Wang, Sian Jin, Quincey Koziol, Zhao Zhang, Qiang Guan, Suren Byna, Sriram Krishnamoorthy, Dingwen Tao
Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights. CLUSTER (2021)
Bo Fang, Daoce Wang, Sian Jin, Quincey Koziol, Zhao Zhang, Qiang Guan, Suren Byna, Sriram Krishnamoorthy, Dingwen Tao
Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights. CoRR (2021)
J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang
KAISA: an adaptive second-order optimizer framework for deep neural networks. SC (2021)
Yang You, Yuhui Wang, Huan Zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh
The Limit of the Batch Size. CoRR (2020)
J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster
Convolutional Neural Network Training with Distributed K-FAC. CoRR (2020)
Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster
Efficient I/O for Neural Network Training with Compressed Data. IPDPS (2020)
J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster
Convolutional neural network training with distributed K-FAC. SC (2020)
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan R. Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
Kira: Processing Astronomy Imagery Using Big Data Technology. IEEE Trans. Big Data 6 (2) (2020)
Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
Fast Deep Neural Network Training on Distributed Systems and Cloud TPUs. IEEE Trans. Parallel Distributed Syst. 30 (11) (2019)
Zhao Zhang, Lei Huang, Ruizhu Huang, Weijia Xu, Daniel S. Katz
Quantifying the Impact of Memory Errors in Deep Learning. CLUSTER (2019)
Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster
Aggregating Local Storage for Scalable Deep Learning I/O. DLS@SC (2019)
Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
ImageNet Training in Minutes. ICPP (2018)
Zhao Zhang, Lei Huang, Uri Manor, Linjing Fang, Gabriele Merlo, Craig Michoski, John Cazes, Niall Gaffney
FanStore: Enabling Efficient and Scalable I/O for Distributed Deep Learning. CoRR (2018)
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
BeeFlow: A Workflow Management System for In Situ Processing across HPC and Cloud Systems. ICDCS (2018)
Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel
100-epoch ImageNet Training with AlexNet in 24 Minutes. CoRR (2017)
Zhao Zhang, Evan R. Sparks, Michael J. Franklin
Diagnosing Machine Learning Pipelines with Fine-grained Lineage. HPDC (2017)
Matteo Turilli, Feng Liu, Zhao Zhang, André Merzky, Michael Wilde, Jon B. Weissman, Daniel S. Katz, Shantenu Jha
Integrating Abstractions to Enhance the Execution of Distributed Applications. IPDPS (2016)
Daniel S. Katz, André Merzky, Zhao Zhang, Shantenu Jha
Application skeletons: Construction and use in eScience. Future Gener. Comput. Syst. 59 (2016)
Zhao Zhang, Daniel S. Katz, André Merzky, Matteo Turilli, Shantenu Jha, Yadu Nand Babuji
Application Skeleton: Generating Synthetic Applications for Infrastructure Research. J. Open Source Softw. 1 (1) (2016)
Tonglin Li, Xiaobing Zhou, Ke Wang, Dongfang Zhao, Iman Sadooghi, Zhao Zhang, Ioan Raicu
A convergence of key-value storage systems from clouds to supercomputers. Concurr. Comput. Pract. Exp. 28 (1) (2016)
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan R. Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
Scientific computing meets big data technology: An astronomy use case. IEEE BigData (2015)
Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox. CIDR (2015)
Zhao Zhang, Kyle Barbary, Frank Austin Nothaft, Evan R. Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter
Scientific Computing Meets Big Data Technology: An Astronomy Use Case. CoRR (2015)
Matteo Turilli, Feng Liu, Zhao Zhang, André Merzky, Michael Wilde, Jon B. Weissman, Daniel S. Katz, Shantenu Jha
Integrating Abstractions to Enhance the Execution of Distributed Applications. CoRR (2015)
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
Rethinking Data-Intensive Science Using Scalable Analytics Systems. SIGMOD Conference (2015)
Zhao Zhang, Daniel S. Katz
Using Application Skeletons to Improve eScience Infrastructure. eScience (2014)
Daniel S. Katz, Zhao Zhang
Special issue on eScience infrastructure and applications. Future Gener. Comput. Syst. 36 (2014)
Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox. CoRR (2014)
Dongfang Zhao, Zhao Zhang, Xiaobing Zhou, Tonglin Li, Ke Wang, Dries Kimpe, Philip H. Carns, Robert B. Ross, Ioan Raicu
FusionFS: Toward supporting data-intensive scientific applications on extreme-scale high-performance computing systems. IEEE BigData (2014)
Tonglin Li, Xiaobing Zhou, Kevin Brandstatter, Dongfang Zhao, Ke Wang, Anupam Rajendran, Zhao Zhang, Ioan Raicu
ZHT: A Light-Weight Reliable Persistent Dynamic Scalable Zero-Hop Distributed Hash Table. IPDPS (2013)
Zhao Zhang, Daniel S. Katz, Timothy G. Armstrong, Justin M. Wozniak, Ian T. Foster
Parallelizing the execution of sequential scripts. SC (2013)
Zhao Zhang, Daniel S. Katz, Michael Wilde, Justin M. Wozniak, Ian T. Foster
MTC envelope: defining the capability of large scale computers in the context of parallel scripting applications. HPDC (2013)
Daniel S. Katz, Timothy G. Armstrong, Zhao Zhang, Michael Wilde, Justin M. Wozniak
Many-Task Computing and Blue Waters CoRR (2012)
Ketan Maheshwari, Allan Espinosa, Daniel S. Katz, Michael Wilde, Zhao Zhang, Ian T. Foster, Scott Callaghan, Philip Maechling
Job and data clustering for aggregate use of multiple production cyberinfrastructures. DICT@HPDC (2012)
Emalayan Vairavanathan, Samer Al-Kiswany, Lauro Beltrão Costa, Zhao Zhang, Daniel S. Katz, Michael Wilde, Matei Ripeanu
A Workflow-Aware Storage System: An Opportunity Study. CCGRID (2012)
Zhao Zhang, Daniel S. Katz, Justin M. Wozniak, Allan Espinosa, Ian T. Foster
Design and analysis of data management in scalable parallel scripting. SC (2012)
Zhao Zhang, Daniel S. Katz, Matei Ripeanu, Michael Wilde, Ian T. Foster
AME: an anyscale many-task computing engine. WORKS@SC (2011)
Timothy G. Armstrong, Zhao Zhang, Daniel S. Katz, Michael Wilde, Ian T. Foster
Scheduling many-task workloads on supercomputers: Dealing with trailing tasks. MTAGS@SC (2010)
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
Middleware support for many-task computing. Clust. Comput. 13 (3) (2010)
Michael Wilde, Ian T. Foster, Kamil Iskra, Peter H. Beckman, Zhao Zhang, Allan Espinosa, Mihael Hategan, Ben Clifford, Ioan Raicu
Parallel Scripting for Applications at the Petascale and Beyond. Computer 42 (11) (2009)
Zhao Zhang, Allan Espinosa, Kamil Iskra, Ioan Raicu, Ian T. Foster, Michael Wilde
Design and Evaluation of a Collective IO Model for Loosely Coupled Petascale Programming CoRR (2009)
Ioan Raicu, Zhao Zhang, Michael Wilde, Ian T. Foster, Peter H. Beckman, Kamil Iskra, Ben Clifford
Towards Loosely-Coupled Programming on Petascale Systems CoRR (2008)
Zhao Zhang, Allan Espinosa, Kamil Iskra, Ioan Raicu, Ian T. Foster, Michael Wilde
Design and evaluation of a collective IO model for loosely coupled petascale programming. MTAGS@SC (2008)
Ioan Raicu, Zhao Zhang, Michael Wilde, Ian T. Foster
Enabling Loosely-Coupled Serial Job Execution on the IBM BlueGene/P Supercomputer and the SiCortex SC5832 CoRR (2008)
Ioan Raicu, Zhao Zhang, Michael Wilde, Ian T. Foster, Peter H. Beckman, Kamil Iskra, Ben Clifford
Toward loosely coupled programming on petascale systems. SC (2008)