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ORCIDZhao Zhang 0007
Person information
- affiliation: University of Texas at Austin, Texas Advanced Computing Center, Austin, TX, USA
- affiliation (former): University of California, Berkeley, AMPLab, CA, USA
- affiliation (former): University of Chicago, Department of Computer Science, Chicago, IL, USA
Other persons with the same name
- Zhao Zhang — disambiguation page
- Zhao Zhang 0001
![[0000-0002-5703-7969]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-5703-7969")
— Hefei University of Technology, School of Computer Science and Information Engineering (School of Artificial Intelligence), China (and 2 more) - Zhao Zhang 0002 — Zhejiang Normal University, College of Mathematics Physics and Information Engineering, Jinhua, China (and 1 more)
- Zhao Zhang 0003 — Northeastern University, School of Information Science and Engineering, Shenyang, China
- Zhao Zhang 0004 — Chinese Academy of Sciences, Institute of Semiconductors, Beijing, China
- Zhao Zhang 0005 — Nanjing Forestry University, Department of Computer Science and Technology, China
- Zhao Zhang 0006 — Heriot-Watt University, Edinburgh, UK (and 1 more)
- Zhao Zhang 0008 — University of Illinois at Chicago, IL, USA
- Zhao Zhang 0009 — Guilin University of Electronic Technology, Guangxi Key Laboratory of Trusted Software, China (and 1 more)
- Zhao Zhang 0010 — Iowa State University, Department of Electrical and Computer Engineering, Ames, IA, USA (and 1 more)
- Zhao Zhang 0011 — Chinese Academy of Sciences, Institute of Computing Technology, Key Lab of Intelligent Information Processing, Beijing, China
- Zhao Zhang 0012 — University of Texas, Health Science Center, San Antonio, TX, USA (and 1 more)
- Zhao Zhang 0013 — Dalian University of Technology, Faculty of Vehicle Engineering and Mechanics, Department of Engineering Mechanics, China
- Zhao Zhang 0014 — Beihang University, School of Transportation Science and Engineering, Beijing, China (and 2 more)
- Zhao Zhang 0015 — Nanchang Hangkong University, School of Information Technology, China
- Zhao Zhang 0016 — North Dakota State University, Department of Agricultural and Biosystems Engineering, Fargo, ND, USA (and 1 more)
- Zhao Zhang 0017 — Tianjin University, School of Precision Instrument and Opto-electronics Engineering, China
- Zhao Zhang 0018 — Nankai University, College of Computer Science, TKLNDST, Tianjin, China (and 1 more)
- Zhao Zhang 0019 — Qilu University of Technology (Shandong Academy of Sciences), School of Electrical Engineering and Automation, Jinan, China
- Zhao Zhang 0020 — Nanjing University of Aeronautics and Astronautics, College of Automation Engineering, China
- Zhao Zhang 0021 — PLA Information Engineering University, Zhengzhou Information Science and Technology Institute, China
- Zhao Zhang 0022 — University of Lorraine, CNRS Loria, Nancy, France
- Zhao Zhang 0023 — Beijing University of Posts and Telecommunication, School of Electronic Engineering, China
- Zhao Zhang 0024 — Tsinghua University, Department of Automation, Beijing, China
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2020 – today
- 2023
[c28]Qiyang Ding, Pengfei Zheng, Shreyas Kudari, Shivaram Venkataraman, Zhao Zhang:
Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning. SC 2023: 25:1-25:13- [c27]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: 95:1-95:12 - [i15]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 abs/2306.11615 (2023) - [i14]Qiyang Ding, Pengfei Zheng, Shreyas Kudari, Shivaram Venkataraman, Zhao Zhang:
Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning. CoRR abs/2306.14086 (2023) - 2022
- [j9]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): 3616-3627 (2022) - 2021
- [c26]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: 409-420 - [c25]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: 13 - [c24]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: 313-331 - [i13]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 abs/2105.12929 (2021) - [i12]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 abs/2107.01739 (2021) - 2020
- [j8]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): 369-381 (2020) - [c23]Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster:
Efficient I/O for Neural Network Training with Compressed Data. IPDPS 2020: 409-418 - [c22]J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster:
Convolutional neural network training with distributed K-FAC. SC 2020: 94 - [i11]Yang You, Yuhui Wang, Huan Zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh:
The Limit of the Batch Size. CoRR abs/2006.08517 (2020) - [i10]J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster:
Convolutional Neural Network Training with Distributed K-FAC. CoRR abs/2007.00784 (2020)
2010 – 2019
- 2019
- [j7]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): 2449-2462 (2019) - [c21]Zhao Zhang, Lei Huang, Ruizhu Huang, Weijia Xu, Daniel S. Katz:
Quantifying the Impact of Memory Errors in Deep Learning. CLUSTER 2019: 1-12 - [c20]Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster:
Aggregating Local Storage for Scalable Deep Learning I/O. DLS@SC 2019: 69-75 - 2018
- [c19]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: 1029-1038 - [c18]Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer:
ImageNet Training in Minutes. ICPP 2018: 1:1-1:10 - [i9]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 abs/1809.10799 (2018) - 2017
- [c17]Zhao Zhang, Evan R. Sparks, Michael J. Franklin:
Diagnosing Machine Learning Pipelines with Fine-grained Lineage. HPDC 2017: 143-153 - [i8]Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel:
100-epoch ImageNet Training with AlexNet in 24 Minutes. CoRR abs/1709.05011 (2017) - 2016
- [j6]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): 44-69 (2016) - [j5]Daniel S. Katz, André Merzky, Zhao Zhang, Shantenu Jha:
Application skeletons: Construction and use in eScience. Future Gener. Comput. Syst. 59: 114-124 (2016) - [j4]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): 17 (2016) - [c16]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: 953-962 - 2015
- [c15]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: 918-927 - [c14]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 - [c13]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: 631-646 - [i7]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 abs/1504.04720 (2015) - [i6]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 abs/1507.03325 (2015) - 2014
- [j3]Daniel S. Katz, Zhao Zhang:
Special issue on eScience infrastructure and applications. Future Gener. Comput. Syst. 36: 335-337 (2014) - [c12]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: 61-70 - [c11]Zhao Zhang, Daniel S. Katz:
Using Application Skeletons to Improve eScience Infrastructure. eScience 2014: 111-118 - [i5]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 abs/1409.3809 (2014) - 2013
- [c10]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: 37-48 - [c9]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: 775-787 - [c8]Zhao Zhang, Daniel S. Katz, Timothy G. Armstrong, Justin M. Wozniak, Ian T. Foster:
Parallelizing the execution of sequential scripts. SC 2013: 31:1-31:12 - 2012
- [c7]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: 326-334 - [c6]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: 3-12 - [c5]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: 85 - [i4]Daniel S. Katz, Timothy G. Armstrong, Zhao Zhang, Michael Wilde, Justin M. Wozniak:
Many-Task Computing and Blue Waters. CoRR abs/1202.3943 (2012) - 2011
- [c4]Zhao Zhang, Daniel S. Katz, Matei Ripeanu, Michael Wilde, Ian T. Foster:
AME: an anyscale many-task computing engine. WORKS@SC 2011: 137-146 - 2010
- [j2]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): 291-314 (2010) - [c3]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: 1-10
2000 – 2009
- 2009
- [j1]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): 50-60 (2009) - [i3]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 abs/0901.0134 (2009) - 2008
- [c2]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: 1-10 - [c1]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: 22 - [i2]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 abs/0808.3536 (2008) - [i1]Ioan Raicu, Zhao Zhang, Michael Wilde, Ian T. Foster, Peter H. Beckman, Kamil Iskra, Ben Clifford:
Towards Loosely-Coupled Programming on Petascale Systems. CoRR abs/0808.3540 (2008)
Coauthor Index
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