2025 Champions
- PRISM: Practical In-Memory Acceleration for Subgraph Matching at Scale – Deting Chen, Yu Huang, Yi Huang, Binbin Lin, Yi Zhang, Long Zheng, Xiaofei Liao, Hai Jin (Huazhong Univ. of Science and Tech.)
- Towards Efficient Sparse Deep Neural Network Inference via Multi-level Concurrency Orchestration – Ming Dun, Jie Zhou (Inst. of Computing Tech, CAS), Huawei Cao (UCAS), Shuhan Song, Yiming Sun, Mingyu Yan, Xiaochun Ye (Inst. of Computing Tech, CAS)
2025 Student Champion
- DBOS Network Sensing: A Web Services Approach to Collaborative Awareness – Sophia Lockton, Jeremy Kepner, Michael Stonebraker, Hayden Jananthan, LaToya Anderson, William Arcand, David Bestor, William Bergeron, Alex Bonn, Daniel Burrill, Chansup Byun (MIT), Timothy Davis (Texas A&M), Vijay Gadepally, Michael Houle, Matthew Hubbell, Michael Jones, Piotr Luszczek, Peter Michaleas, Lauren Milechin, Chasen Milner, Guillermo Morales, Julie Mullen (MIT), Michel Pelletier (OneSparse), Alex Poliakov (DBOS), Andrew Prout, Albert Reuther, Antonio Rosa, Charles Yee, Alex Pentland (MIT)
2025 Innovation Awards
- Scaling Triangle Counting and K-Truss on the UpDown Architecture – Jiya Su, Alexander Fell, Andronicus Rajasukumar (Univ. of Chicago), David F. Gleich (Purdue Univ.), Andrew A. Chien (Univ. of Chicago)
- Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software – Siddharth Samsi, Dan Campbell, Emanuel Scoullos, Oded Green (NVIDIA)
2025 Student Innovation Award
- Anonymized Network Sensing using C++26 std::execution on GPUs – Michael Mandulak (RPI), Sayan Ghosh, S M Ferdous, Mahantesh Halappanavar (PNNL), George Slota (RPI)
2025 Honorable Mentions
- InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections – Meng Qin (Pengcheng Laboratory), Weihua Li (Beihang Univ.), Jinqiang Cui (Pengcheng Laboratory), Sen Pei (Columbia Univ.)
- SANST: Sensing Anonymized Network via Sorted Triplets – Jianyu Wang, Wenzi Tang, Chenglong Shi, Zhe Zhang (Guangxi Univ.), Dan Chen (National Univ. Singapore), Miaojiang Chen, Wenjing Xiao (Guangxi Univ.)
- BUG: Balanced DFS-Based Subgraph Matching with a Reuse Strategy on GPUs – Zicang Xu, Lei Zou (Peking Univ.)
2024 Champions
- Mercury: Efficient Subgraph Matching on GPUs with Hybrid Scheduling – Zhiheng Lin (Inst. of Computing Tech, CAS), Changjie Xu (UCAS), Ke Meng, Guangming Tan (Inst. of Computing Tech, CAS)
- Towards Faster Graph Partitioning via Pre-training and Inductive Inference – Meng Qin (HKUST), Chaorui Zhang (Huawei), Yu Gao (Independent), Yibing Ding, Weipeng Jiang (Huawei), Weixi Zhang (Huawei Technologies), Wei Han (Huawei), Bo Bai (Huawei Technologies)
2024 Innovation Awards
- Distributed-Memory Sparse Deep Neural Network Inference Using Global Arrays – Sayan Ghosh, Bruce Palmer, Andres Marquez (PNNL)
- Extracting TCPIP Headers at High Speed for the Anonymized Network Traffic Graph Challenge – Zhaoyang Han, Andrew Briasco-Stewart (Northeastern Univ.), Michael Zink (UMass Amherst), Miriam Leeser (Northeastern Univ.)
2024 Honorable Mention
- Sans: Streaming Anonymized Network Sensing – Ketai Zhao, Yuhang Zhou, Hong Xu Pan, Zhibin Wang, Sheng Zhong, Chen Tian (Nanjing Univ.)
2023 Champions
- Adaptive Sparse Deep Neural Network Inference on Resource-Constrained Cost-Efficient GPUs – Ming Dun, Xu Zhang, Huawei Cao, Yuan Zhang, Junying Huang, Xiaochun Ye (Inst. of Computing Tech, CAS)
- An Integrated Approach to Accelerating Stochastic Block Partitioning – Frank D Wanye (Virginia Tech), Vitaliy Gleyzer, Edward Kao (MIT Lincoln Laboratory), Wu-chun Feng (Virginia Tech)
- SMOG: Accelerating Subgraph Matching on GPUs – Zhibin Wang, Ziheng Meng (Nanjing Univ.), Xue Li (Alibaba), Xi Lin (NJU), Long Zheng (Huazhong Univ. of Science and Tech.), Chen Tian, Sheng Zhong (Nanjing Univ.)
2023 Innovation Awards
- GLARE: Accelerating Sparse DNN Inference Kernels with Global Memory Access Reduction – Shui Jiang (Chinese Univ. of Hong Kong), Tsung-Wei Huang (Univ. of Wisconsin), Tsung-Yi Ho (Chinese Univ. of Hong Kong)
- uSAP: An Ultra-Fast Stochastic Graph Partitioner – Chih-Chun Chang, Tsung-Wei Huang (Univ. of Wisconsin)
- RaftGP: Random Fast Graph Partitioning – Yu Gao (Huawei Technologies), Meng Qin (HKUST), Yibin Ding, Li Zeng, Chaorui Zhang, Weixi Zhang, Wei Han, Rongqian Zhao, Bo Bai (Huawei Technologies)
- Fast Triangle Counting – David A Bader (New Jersey Inst. of Tech.)
2023 Student Innovation Awards
- Triangle Counting Through Cover-Edges – David A Bader, Fuhuan Li, Anya Ganeshan, Ahmet Gundogdu, Jason Lew, Oliver Alvarado Rodriguez, Zhihui Du (New Jersey Inst. of Tech.)
2023 Honorable Mention
- Decontentioned Stochastic Block Partition – Ahsen J Uppal (George Washington Univ.), Thomas Rolinger (Laboratory for Physical Sciences), H. Howie Huang (George Washington Univ.)
2022 Champions
- Accelerating Sparse Deep Neural Network Inference Using GPU Tensor Cores – Yufei Sun, Long Zheng, Qinggang Wang, Xiangyu Ye, Yu Huang, Pengcheng Yao, Xiaofei Liao, Hai Jin (Huazhong Univ. of Science and Technology)
- Towards Fast GPU-based Sparse DNN Inference: A Hybrid Compute Model – Shaoxian Xu, Minkang Wu, Long Zheng, Zhiyuan Shao, Xiangyu Ye, Xiaofei Liao, Hai Jin (Huazhong Univ. of Science and Technology)
2022 Innovation Awards
- FAST: A Scalable Subgraph Matching Framework over Large Graphs – Jiezhong He, Zhouyang Liu, Yixin Chen, Hengyue Pan, Zhen Huang, Dongsheng Li (NUDT)
- HTC: Hybrid Vertex-parallel and Edge-parallel Triangle Counting – Li Zeng, Kang Yang, Haoran Cai, Jinhua Zhou, Rongqian Zhao, Xin Chen (Huawei Technologies)
- Improved Distributed-Memory Triangle Counting by Exploiting the Graph Structure – Sayan Ghosh (Washington State Univ.)
- Kalman Filter Driven Estimation of Community Structure in Time Varying Graphs – Lisa JK Durbeck, Peter Athanas (Virginia Tech)
2022 Honorable Mention
- Sparse Deep Neural Network Inference Using Different Programming Models – Hyungro Lee, Milan Jain (PNNL), Sayan Ghosh (Washington State Univ.)
2021 Champions
- Fast Sparse Deep Neural Network Inference with Flexible SpMM Optimization Space Exploration – Jie Xin, Xianqi Ye, Long Zheng, Qinggang Wang, Yu Huang, Pengcheng Yao, Linchen Yu, Xiaofei Liao, Hai Jin (Huazhong University of Science and Technology)
- Faster Stochastic Block Partition using Aggressive Initial Merging, Compressed Representation, and Parallelism Control – Ahsen J Uppal, Jaeseok Choi (George Washington Univ.), Thomas Rolinger (Univ. of Maryland College Park), H. Howie Huang (George Washington Univ.)
2021 Innovation Awards
- Towards Distributed Square Counting in Large Graphs – Trevor Steil, Geoffrey Sanders, Roger Pearce (Lawrence Livermore National Laboratory)
- Sparse Deep Neural Network Acceleration on HBM-Enabled FPGA Platform – Abhishek K Jain, Sharan Kumar, Aashish Tripathi, Dinesh Gaitonde (Xilinx)
- Productive High-Performance k-Truss Decomposition on GPU Using Linear Algebra – Wang Runze, Linchen Wu, Qinggang Wang, Jie Xin, Long Zheng (Huazhong University of Science and Technology)
2021 Student Innovation Awards
- HyKernel: A Hybrid Selection of One/Two-Phase Kernels for Triangle Counting on GPUs – Mohammad Almasri, Neo Vasudeva, Rakesh Nagi (Univ. of Illinois Urbana-Champaign), Jinjun Xiong (IBM), Wen-Mei Hwu (Univ. of Illinois Urbana-Champaign, Nvidia)
2021 Honorable Mention
- DPGS Graph Summarization Preserves Community Structure – Lisa JK Durbeck; Peter Athanas (Virginia Tech)
2020 Champions
- Scaling Graph Clustering with Distributed Sketches – Benjamin Priest (LLNL), Alec Dunton (CU Boulder), Geoffrey Sanders (LLNL)
- At-Scale Sparse Deep Neural Network Inference With Efficient GPU Implementation – Mert Hidayetoglu, Carl Pearson, Vikram Sharma Mailthody (UIUC), Eiman Ebrahimi (Nvidia), Jinjun Xiong (IBM)), Rakesh Nagi, Wen-mei W. Hwu (UIUC)
- A Novel Inference Algorithm for Large Sparse Neural Network using Task Graph Parallelism – Dian-Lun Lin, Tsung-Wei Huang (Univ of Utah)
- TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure – Sayan Ghosh, Mahantesh Halappanavar (PNNL)
2020 Innovation Awards
- Combinatorial Tiling for Sparse Neural Networks – Filip Pawłowski (ENS Lyon), Rob H. Bisseling (Utrecht), Bora Ucar (CNRS), Albert-Jan Yzelman (Huawei)
- Studying the Effects of Hashing of Sparse Deep Neural Networks on Data and Model Parallelisms – Mohammad Hasanzadeh Mofrad, Rami Melhem (Univ of Pittsburgh), Yousuf Ahmad, Mohammad Hammoud (CMU Qatar)
- Incremental Streaming Graph Partitioning – Lisa Durbeck, Peter Athanas (Virginia Tech)
2020 Honorable Mention
- KTRUSSEXPLORER: Exploring the Design Space of K-truss Decomposition Optimizations on GPUs – Safaa Diab, Mhd Ghaith Olabi, Izzat El Hajj (American University of Beirut)
- Analysis of Floating-Point Round-Off Error in Linear Algebra Routines for Graph Clustering – L. Minah Yang (CU Boulder), Alyson Fox (LLNL)
2019 Champions
- One Quadrillion Triangles Queried on One Million Processors – Roger Pearce, Trevor Steil, Benjamin Priest, Geoffrey Sanders (Lawrence Livermore National Laboratory)
- H-INDEX: Hash-Indexing for Parallel Triangle Counting on GPUs – Santosh Pandey (Stevens Institute of Tech.), Xiaoye Li, Aydin Buluc (Lawrence Berkeley National Laboratory), Jiejun Xu (HRL), Hang Liu (Stevens Institute of Tech.)
- Exploration of Fine-Grained Parallelism for Load Balancing Eager K-truss on GPU and CPU – Mark P Blanco (Carnegie Mellon University and Sandia National Labs), Tze Meng Low (Carnegie Mellon University), Kyungjoo Kim (Sandia National Labs)
- A GPU Implementation of the Sparse Deep Neural Network Graph Challenge – Mauro Bisson, Massimiliano Fatica (NVIDIA)
- Write Quick, Run Fast: Sparse Deep Neural Network in 20 Minutes of Development Time via SuiteSparse: GraphBLAS – Timothy A Davis, Mohsen Aznaveh, Scott Kolodziej (Texas A&M University)
2019 Innovation Awards
- Linear Algebra-Based Triangle Counting via Fine-Grained Tasking on Heterogeneous Environments – Abdurrahman Yaşar (Georgia Institute of Technology), Siva Rajamanickam, Jonathan Berry, Michael M Wolf (Sandia National Laboratories), Jeffrey Young, Ümit V. Çatalyürek (Georgia Institute of Technology)
- Scalable Triangle Counting on Distributed-Memory Systems – Seher Acer (Sandia National Laboratories), Abdurrahman Yaşar (Georgia Institute of Technology), Siva Rajamanickam, Michael M Wolf (Sandia National Laboratories), Ümit V. Çatalyürek (Georgia Institute of Technology)
- Scaling and Quality of Modularity Optimization Methods for Graph Clustering – Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo (Pacific Northwest National Laboratory), Ananth Kalyanaraman (Washington State University)
- Distributed Direction-Optimizing Label Propagation for Community Detection – Xu Liu (Washington State University); Jesun S Firoz, Marcin Zalewski, Mahantesh Halappanavar, Kevin Barker, Andrew Lumsdaine (Pacific Northwest National Laboratory), Assefaw H Gebremedhin (Washington State University)
- Scalable Inference for Sparse Deep Neural Networks using Kokkos Kernels – John A Ellis, Sivasankaran Rajamanickam (Sandia National Laboratories)
2019 Student Innovation Awards
- DistTC: High Performance Distributed Triangle Counting – Loc Hoang, Vishwesh Jatala, Xuhao Chen, Udit Agarwal, Roshan Dathathri, Gurbinder S Gill, Keshav Pingali (The University of Texas at Austin)
- Fast Stochastic Block Partitioning via Sampling – Frank D Wanye (Virginia Tech), Vitaliy Gleyzer (MIT Lincoln Laboratory), Wu-chun Feng (Virginia Tech)
- Update on k-truss Decomposition on GPU – Mohammad Almasri, Omer Anjum, Carl Pearson, Zaid Qureshi, Vikram Sharma Mailthody, Rakesh Nagi (University of Illinois at Urbana-Champaign), Jinjun Xiong (IBM Thomas J. Watson Research Center); Wen-Mei Hwu (UIUC)
- Accelerating DNN Inference with GraphBLAS and the GPU – Xiaoyun Wang , Zhongyi Lin, Carl Yang, John D Owens (University of California, Davis)
2019 Finalists
- Fast Parallel BFS-Based Triangle Counting on GPUs – Leyuan Wang, John D Owens (Univeristy of California, Davis)
- Performance of Training Sparse Deep Neural Networks on GPUs – JIANZONG WANG (平安科技（深圳）有限公司); Zhangcheng Huang (Ping An Technology (Shenzhen) Co., Ltd); Lingwei Kong (PingAn Tech); Jing Xiao (Ping An Insurance (Group) Company of China); Pengyu Wang (Shanghai Jiao Tong University); Lu Zhang (Shanghai Jiao Tong University); Chao Li (Shanghai Jiaotong University)
2019 Honorable Mention
- Fast Triangle Counting on GPU – Chuangyi Gui, Long Zheng, Pengcheng Yao, Xiaofei Liao, Hai Jin (Huazhong University of Science and Technology)
- Update on Triangle Counting on GPU – Carl Pearson, Mohammad Almasri, Vikram Sharma Mailthody, Zaid Qureshi, Omer Anjum, Wen-Mei Hwu (University of Illinois at Urbana-Champaign), Jinjun Xiong (IBM Thomas J. Watson Research Center); Rakesh Nagi (UIUC)
- Multithreaded Layer-wise Training of Sparse Deep Neural Networks using Compressed Sparse Column – Mohammad Hasanzadeh Mofrad, Rami Melhem (University of Pittsburgh), Yousuf Ahmad, Mohammad Hammoud (Carnegie Mellon University in Qatar)
- Accelerating Sparse Deep Neural Network on FPGA – Sitao Huang, Carl Pearson, Rakesh Nagi, (University of Illinois at Urbana-Champaign), Jinjun Xiong (IBM Thomas J. Watson Research Center), Deming Chen, Wen-Mei Hwu (University of Illinois at Urbana-Champaign)
2018 Champions
- Fast Triangle Counting Using Cilk – Abdurrahman Yasar, Sivasankaran Rajamanickam, Michael Wolf, Jonathan Berry (Sandia), Umit V. Catalyurek (Georgia Tech)
- High-Performance Triangle Counting on GPUs – Yang Hu (GWU), Hang Liu (UMass Lowell), H. Howie Huang (GWU)
Update on Static Graph Challenge on GPU – Mauro Bisson, Massimiliano Fatica (Nvidia)
K-truss decomposition for Scale-Free Graphs at Scale in Distributed Memory – Roger Pearce, Geoffrey Sanders (LLNL)
2018 Finalists
- Fast and Adaptive List Intersections on the GPU – James Fox, Oded Green, Kasimir Gabert, Xiaojing An, David Bader (Georgia Tech)
- Collaborative (CPU + GPU) Algorithms for Triangle Counting and Truss Decomposition – Vikram S. Mailthody, Ketan Date, Zaid Qureshi, Carl Pearson, Rakesh Nagi (UIUC), Jinjun Xiong (IBM), Wen-mei Hwu (UIUC)
- Preliminary Exploration on Large-Scale Triangle Counting in Shared-Memory Multicore System – Jiyuan Zhang, Franz Franchetti
- Linear Algebraic Formulation of Edge-centric K-truss Algorithms with Adjacency Matrices – Meng Low, Daniele G. Spampinato, Anurag Kutuluru, Upasana Sridhar, Doru Thom Popovici, Franz Franchetti, Scott McMillan (CMU)
Discovering k-Trusses in Large-Scale Network – Alessio Conte (NII Tokyo), Daniele De Sensi, Roberto Grossi, Andrea Marino, Luca Versari (Universita di Pisa)
2018 Innovation Awards
- Graph algorithms via SuiteSparse:GraphBLAS: triangle counting and K-truss – Timothy A. Davis (Texas A&M)
- Logarithmic Radix Binning and Vectorized Triangle Counting – Oded Green, James Fox, Alex Watkins, Alok Tripathy, Kasimir Gabert, Euna Kim, Xiaojing An, Kumar Aatish, David Bader (Georgia Tech)
- Investigation of Spectral Clustering for Signed Graph Matrix Representations – Alyson Fox, Geoffrey Sanders (LLNL), Andrew Knyazev (CU Denver)
2018 Student Innovation Awards
- PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV – Fazle Sadi, Joe Sweeney, Scott McMillan, Tze Meng Low, James C. Hoe, Larry Pileggi, Franz Franchetti (CMU)
- Scalable Distributed Memory Community Detection Using Vite – Sayan Ghosh (Wash St), Mahantesh Halappanavar, Antonino Tumeo (PNNL), Ananth Kalyanaraman, Assefaw H. Gebremedhin (Wash St)
- Triangle Counting and Truss Decomposition using FPGA – Sitao Huang, Mohamed El-Hadedy, Cong Hao, Qin Li, Vikram S. Mailthody, Ketan Date (UIUC),
Jinjun Xiong (IBM), Deming Chen, Rakesh Nagi, Wen-mei Hwu (UIUC) Fast Stochastic Block Partition for Streaming Graphs – Ahsen J. Uppal, H. Howie Huang (GWU)
2018 Honorable Mention
- Estimating Edge-Local Triangle Count Heavy Hitters in Edge-Linear Time and Almost-Vertex-Linear Space – Benjamin W. Priest (Dartmouth), Roger Pearce, Geoffrey Sanders (LLNL)
- Triangle Counting with A Multi-Core Computer – Evan Donato, Ming Ouyang, Cristian Peguero-Isalguez (UMass Boston)
- Parallel Counting of Triangles in Large Graphs: Pruning and Hierarchical Clustering Algorithms – Chun-Yen Kuo, Ching Nam Hang, Pei-Duo Yu, Chee Wei Tan (CU Hong Kong)
Analysis of all 2017 Triangle Counting Submissions
2017 Champions
- Fast Linear Algebra-Based Triangle Counting with KokkosKernels – Michael Wolf, Mehmet Deveci, Jonathan Berry, Simon Hammond, Sivasankaran Rajamanickam (Sandia)
- Triangle Counting for Scale-Free Graphs at Scale in Distributed Memory – Roger Pearce (LLNL)
- Scalable Static and Dynamic Community Detection Using Grappolo – Mahantesh Halappanavar (PNNL), Hao Lu (ORNL), Ananth Kalyanaraman (Wash St), Antonino Tumeo (PNNL)
- Parallel Triangle Counting and k-Truss Identification using Graph-centric Methods – Chad Voegele, Yi-Shan Lu, Sreepathi Pai, Keshav Pingali (UT Austin)
- Static Graph Challenge on GPU – Mauro Bisson, Massimiliano Fatica (NVIDIA)
2017 Finalists
- Truss Decomposition on Shared-Memory Parallel Systems – Shaden Smith (UMN, Intel), Xing Liu, Nesreen K. Ahmed (Intel), Ancy Sarah Tom (UMN), Fabrizio Petrini (Intel), George Karypis (UMN)
- Exploring Optimizations on Shared-memory Platforms for Parallel Triangle Counting Algorithms – Ancy Sarah Tom (UMN), Narayanan Sundaram, Nesreen Ahmed, Shaden Smith, Stijn Eyerman, Midhunchandra Kodiyath, Ibrahim Hur, Fabrizio Petrini (Intel), George Karypis (UMN)
- TriX: Triangle Counting at Extreme Scale – Yang Hu, Pradeep Kumar (GWU), Guy Swope (Raytheon), H. Howie Huang (GWU)
2017 Innovation Awards
- An Ensemble Framework for Detecting Community Changes in Dynamic Networks – Timothy La Fond, Geoffrey Sanders, Christine Klymko, Van Emden Henson (LLNL)
- Quickly Finding a Truss in a Haystack – Oded Green, James Fox, Euna Kim (Georgia Tech), Federico Busato, Nicola Bombieri (Univ Verona), Kartik Lakhotia, Shijie Zhou, Shreyas Singapura, Hanqing Zeng, Rajgopal Kannan, Viktor Prasanna (USC), David Bader (Georgia Tech)
2017 Student Innovation Awards
- Parallel k-Truss Decomposition on Multicore Systems – Humayun Kabir, Kamesh Madduri (Penn State)
- Preconditioned Spectral Clustering for Stochastic Block Partition Streaming Graph Challenge – David Zhuzhunashvili (UC Boulder), Andrew Knyazev (Mitsubishi Electric Research Laboratories (MERL))
- Design and Implementation of Parallel PageRank on Multicore Platforms – Shijie Zhou, Kartik Lakhotia, Shreyas G. Singapura, Hanqing Zeng, Rajgopal Kannan, Viktor Prasanna (USC), James Fox, Eun Kim, Oded Green, David Bader (Georgia Tech)
2017 Honorable Mention
- Distributed Triangle Counting in the Graphulo Matrix Math Library – Dylan Hutchison (University of Washington)
- First Look: Linear Algebra-Based Triangle Counting without Matrix Multiplication – Tze Meng Low, Varun Nagaraj Rao, Matthew Lee, Doru Popovici, Franz Franchetti (CMU), Scott McMillan (SEI)
- Scalable Stochastic Block Partition – Ahsen Uppal (GWU), Guy Swope (Raytheon), and H. Howie Huang (GWU)
- Superstrider Associative Array Architecture – Erik DeBenedictis, Jeanine Cook (Sandia), Sriseshan Srikanth, Thomas Conte (Georgia Tech)
- Triangle Counting Via Vectorized Set Intersection – Shahir Mowlaei (University of Pittsburgh)
- Collaborative (CPU + GPU) Algorithms for Triangle Counting and Truss Decomposition on the Minsky Architecture – Ketan Date, Keven Feng, Rakesh Nagi (UIUC), Jinjun Xiong (IBM), Nam Sung Kim, Wen-Mei Hwu (UIUC)