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Peng Jiang 0004

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affiliation: University of Iowa, Iowa City, IA, USA
affiliation (PhD 2019): Ohio State University, Department of Computer Science and Engineering, OH, USA

Other persons with the same name

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Peng Jiang — disambiguation page
Peng Jiang 0001 — Queen Mary University of London, UK
Peng Jiang 0002 — Kwai Inc. / Kuaishou Inc., Beijing, China (and 3 more)
Peng Jiang 0005 — University of Illinois Urbana-Champaign, Department of Computer Science, IL, USA
Peng Jiang 0006 — National Cancer Institute, Bethesda, MD, USA (and 2 more)
Peng Jiang 0007 — Beijing Institute of Technology, School of Cyberspace Science and Technology, Beijing, China
Peng Jiang 0008 — Kuaishou Technology, Beijing, China
Peng Jiang 0009 — Yiwu Industrial and Commercial College, Jinhua, China (and 1 more)
Peng Jiang 0010 — Kunming Shipborne Equipment Research & Test Center, China
Peng Jiang 0011 — Tsinghua University, Department of Automation, Beijing, China

Peng Jiang 0012 — Dalian University of Technology, School of Information and Communication Engineering, China
Peng Jiang 0013 — Chinese Academy of Sciences, National Astronomical Observatories, Beijing, China (and 2 more)
Peng Jiang 0014 — China Railway Signal & Communication Metro-Transportation Control Technology Co., Ltd., China
Peng Jiang 0015 — Cleveland State University, Center for Gene Regulation in Health and Disease, OH, USA (and 3 more)
Peng Jiang 0016 — Hangzhou Normal University, School of Information Science and Engineering, China (and 1 more)
Peng Jiang 0017 — Anhui University, School of Resources and Environmental Engineering, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Hefei, China (and 1 more)
Peng Jiang 0018 — Wuhan University of Technology, School of Mechanical and Electrical Engineering, China
Peng Jiang 0019 — Texas A&M University, College Station, TX, USA
Peng Jiang 0020 — Tsinghua University, Department of Precision Instrument, Beijing, China
Peng Jiang 0021 — Liaoning ATS Intelligent Transportation Technology Company Ltd., Shenyang, China
Peng Jiang 0022 — Huazhong University of Science and Technology, School of Mechanical Science & Engineering, Wuhan, China
Peng Jiang 0023 — Shandong University, School of Business, Weihai, China
Peng Jiang 0024 — SurveyMonkey, San Mateo, CA, USA
Peng Jiang 0025 — Wuhan University, Institute of Artificial Intelligence, School of Computer Science, China
Peng Jiang 0026 — Heilongjiang Bayi Agricultural University, College of Information and Electrical Engineering, Daqing, China
Peng Jiang 0027 — Old Dominion University, Department of Electrical and Computer Engineering, School of Cybersecurity, Norfolk, VA, USA
Peng Jiang 0028 — Guilin University of Electronic Technology, School of Information and Communication, China
Peng Jiang 0030 — Ocean University of China, Network and Information Center, Qingdao, China
Peng Jiang 0031 — Wuhan University, GNSS Research Center, China
Peng Jiang 0032 — Xi'an Jiaotong University, State Key Laboratory for Strength and Vibration of Mechanical Structures, China
Peng Jiang 0033 — Tongji University, College of Surveying and Geo-Informatics, Shanghai, China
Peng Jiang 0034 — Chongqing University of Technology, College of Mechanical Engineering, China
Peng Jiang 0035 — Hohai University, School of Mathematics, Nanjing, China
Peng Jiang 0036 — Sichuan University, Department of Industrial Engineering and Management, Business School, Chengdu, China

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2020 – today

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2025
[c29]
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Shihui Song, Robert Underwood, Sheng Di, Yafan Huang, Peng Jiang, Franck Cappello:
A Memory-Efficient and Computation-Balanced Lossy Compressor on Wafer-Scale Engine. IPDPS 2025: 1-13
[c28]
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Lihan Hu, Peng Jiang:
Improving Accuracy and Efficiency of Graph Embedding Training with Fine-Grained Parameter Management. IPDPS 2025: 737-748
[c27]
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Yihua Wei, Lihan Hu, Peng Jiang:
Matcha: A Language and Compiler for Backtracking-Based Subgraph Matching. IPDPS 2025: 1154-1165
[c26]
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Franck Cappello, Robert Underwood, Yuri Alexeev, Allison H. Baker, Ebru Bozdag, Martin Burtscher, Kyle Chard, Sheng Di, Kyle Gerard Felker, Paul Christopher O'Grady, Hanqi Guo, Yafan Huang, Peng Jiang, Sian Jin, Petter Johansson, Shaomeng Li, Xin Liang, Erik Lindahl, Peter Lindstrom, Zarija Lukic, Magnus Lundborg, Danylo Lykov, Masaru Nagaso, Kento Sato, Amarjit Singh, Seung Woo Son, Shihui Song, William Tang, Dingwen Tao, Jiannan Tian, Kazutomo Yoshii, Kai Zhao:
What to Support When You're Compressing: The State of Practice Gaps and Opportunities for Scientific Data Compression. SC 2025: 1966-1979
[i5]
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  - journals/corr/abs-2503-20031
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Franck Cappello, Allison H. Baker, Ebru Bozdag, Martin Burtscher, Kyle Chard, Sheng Di, Paul Christopher O'Grady, Peng Jiang, Shaomeng Li, Erik Lindahl, Peter Lindstrom, Magnus Lundborg, Kai Zhao, Xin Liang, Masaru Nagaso, Kento Sato, Amarjit Singh, Seung Woo Son, Dingwen Tao, Jiannan Tian, Robert Underwood, Kazutomo Yoshii, Danylo Lykov, Yuri Alexeev, Kyle Gerard Felker:
Lossy Compression of Scientific Data: Applications Constrains and Requirements. CoRR abs/2503.20031 (2025)
2024
[c25]
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Shihui Song, Yafan Huang, Peng Jiang, Xiaodong Yu, Weijian Zheng, Sheng Di, Qinglei Cao, Yunhe Feng, Zhen Xie, Franck Cappello:
CereSZ: Enabling and Scaling Error-bounded Lossy Compression on Cerebras CS-2. HPDC 2024: 309-321
[c24]
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Lihan Hu, Jing Li, Peng Jiang:
cuKE: An Efficient Code Generator for Score Function Computation in Knowledge Graph Embedding. IPDPS 2024: 903-914
[c23]
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Yihua Wei, Peng Jiang:
GCSM: GPU-Accelerated Continuous Subgraph Matching for Large Graphs. IPDPS 2024: 1046-1057
2023
[c22]
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Yang Xia, Peng Jiang, Gagan Agrawal, Rajiv Ramnath:
End-to-End LU Factorization of Large Matrices on GPUs. PPoPP 2023: 288-300
[i4]
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  - journals/corr/abs-2306-10257
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Jiya Su, Peng Jiang, Rujia Wang:
PIMMiner: A High-performance PIM Architecture-aware Graph Mining Framework. CoRR abs/2306.10257 (2023)
2022
[c21]
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Peng Jiang, Yihua Wei, Jiya Su, Rujia Wang, Bo Wu:
SampleMine: A Framework for Applying Random Sampling to Subgraph Pattern Mining through Loop Perforation. PACT 2022: 185-197
[c20]
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Shihui Song, Peng Jiang:
Rethinking graph data placement for graph neural network training on multiple GPUs. ICS 2022: 39:1-39:10
[c19]
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Yang Xia, Peng Jiang, Gagan Agrawal, Rajiv Ramnath:
Scaling and Selecting GPU Methods for All Pairs Shortest Paths (APSP) Computations. IPDPS 2022: 190-200
[c18]
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Peng Jiang, Lihan Hu, Shihui Song:
Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training. NeurIPS 2022
[c17]
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Shihui Song, Peng Jiang:
Rethinking graph data placement for graph neural network training on multiple GPUs. PPoPP 2022: 455-456
[c16]
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Yihua Wei, Peng Jiang:
STMatch: Accelerating Graph Pattern Matching on GPU with Stack-Based Loop Optimizations. SC 2022: 53:1-53:13
2021
[j2]
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Jiya Su, Linfeng He, Peng Jiang, Rujia Wang:
Exploring PIM Architecture for High-Performance Graph Pattern Mining. IEEE Comput. Archit. Lett. 20(2): 114-117 (2021)
[c15]
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Yang Xia, Peng Jiang, Gagan Agrawal, Rajiv Ramnath:
Scaling Sparse Matrix Multiplication on CPU-GPU Nodes. IPDPS 2021: 392-401
[i3]
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Peng Jiang, Rujia Wang, Bo Wu:
An Efficient Graph Mining System for Large Patterns. CoRR abs/2101.07690 (2021)
[i2]
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  - journals/corr/abs-2101-07706
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Peng Jiang, Masuma Akter Rumi:
Communication-Efficient Sampling for Distributed Training of Graph Convolutional Networks. CoRR abs/2101.07706 (2021)
2020
[j1]
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Peng Jiang, Yang Xia, Gagan Agrawal:
Combining SIMD and Many/Multi-core Parallelism for Finite-state Machines with Enumerative Speculation. ACM Trans. Parallel Comput. 7(3): 15:1-15:26 (2020)
[c14]
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Masuma Akter Rumi, Xiaolong Ma, Yanzhi Wang, Peng Jiang:
Accelerating Sparse CNN Inference on GPUs with Performance-Aware Weight Pruning. PACT 2020: 267-278
[c13]
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Yang Xia, Peng Jiang, Gagan Agrawal:
Scaling out speculative execution of finite-state machines with parallel merge. PPoPP 2020: 160-172
[c12]
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Peng Jiang, Changwan Hong, Gagan Agrawal:
A novel data transformation and execution strategy for accelerating sparse matrix multiplication on GPUs. PPoPP 2020: 376-388
[i1]
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  - journals/corr/abs-2007-06134
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Peng Jiang, Gagan Agrawal:
Adaptive Periodic Averaging: A Practical Approach to Reducing Communication in Distributed Learning. CoRR abs/2007.06134 (2020)

2010 – 2019

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2019
[c11]
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Gangyi Zhu, Peng Jiang, Gagan Agrawal:
A Methodology for Characterizing Sparse Datasets and Its Application to SIMD Performance Prediction. PACT 2019: 445-456
[c10]
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Yang Xia, Peng Jiang, Gagan Agrawal:
Enabling prefix sum parallelism pattern for recurrences with principled function reconstruction. CC 2019: 17-28
[c9]
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Peng Jiang, Gagan Agrawal:
Accelerating distributed stochastic gradient descent with adaptive periodic parameter averaging: poster. PPoPP 2019: 403-404
2018
[c8]
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Peng Jiang, Linchuan Chen, Gagan Agrawal:
Revealing parallel scans and reductions in recurrences through function reconstruction. PACT 2018: 10:1-10:13
[c7]
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Peng Jiang, Gagan Agrawal:
Conflict-free vectorization of associative irregular applications with recent SIMD architectural advances. CGO 2018: 175-187
[c6]
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Peng Jiang, Gagan Agrawal:
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication. NeurIPS 2018: 2530-2541
[c5]
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Peng Jiang, Gagan Agrawal:
Revealing parallel scans and reductions in sequential loops through function reconstruction. PPoPP 2018: 395-396
2017
[c4]
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Peng Jiang, Gagan Agrawal:
Efficient SIMD and MIMD parallelization of hash-based aggregation by conflict mitigation. ICS 2017: 24:1-24:11
[c3]
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Peng Jiang, Gagan Agrawal:
Combining SIMD and Many/Multi-core Parallelism for Finite State Machines with Enumerative Speculation. PPoPP 2017: 179-191
2016
[c2]
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Linchuan Chen, Peng Jiang, Gagan Agrawal:
Exploiting recent SIMD architectural advances for irregular applications. CGO 2016: 47-58
[c1]
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Peng Jiang, Linchuan Chen, Gagan Agrawal:
Reusing Data Reorganization for Efficient SIMD Parallelization of Adaptive Irregular Applications. ICS 2016: 16:1-16:10

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