Laxman Dhulipala
research interests
scalable parallel algorithms, algorithm engineering, and vector search.
contactemail: laxman [at] umd.edu CV -- GitHub -- Hobbies
I am an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park, and a research scientist at Google Research with the Graph Mining team.
I obtained my Ph.D. from Carnegie Mellon University, where I was advised by Guy Blelloch, and was a postdoc at MIT working with Julian Shun.
I am broadly interested in efficient parallel algorithms, e.g., for parallel clustering, parallel graph processing, and vector search. I am also interested in models of parallel computation motivated by emerging hardware and exploring these models theoretically and practically.
Students
- Quinten De Man
- Kishen Gowda (co-advised with Aravind Srinivasan)
- Peter Li
- Tobias Rubel
- Zhongqi Wang
- Richard Wen
Teaching
- F26: CMSC451: Design and Analysis of Computer Algorithms
- S26: CMSC451: Design and Analysis of Computer Algorithms
- S25: CMSC858P: Shared-Memory Algorithms
- F24: CMSC451: Design and Analysis of Computer Algorithms
- S24: CMSC858N, Scalable Parallel Algorithms and Data Structures
- F23: CMSC451: Design and Analysis of Computer Algorithms
- S23: CMSC858N, Scalable Parallel Algorithms and Data Structures
- F22: CMSC451: Design and Analysis of Computer Algorithms
Publications
PiPNN: Ultra-Scalable Graph-Based Nearest Neighbor Indexing
[pdf] [arxiv] [code]
Tobias Rubel, Richard Wen, Laxman Dhulipala, Lars Gottesbüren, Rajesh Jayaram, and Jakub Łącki
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026.
Best Research Paper Award
[pdf] [arxiv] [code]
Tobias Rubel, Richard Wen, Laxman Dhulipala, Lars Gottesbüren, Rajesh Jayaram, and Jakub Łącki
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026.
Best Research Paper Award
Turbocharging PiPNN for Proximity and $k$-NN Graph Building
[pdf]
Tobias Rubel, Richard Wen, Guy Blelloch, Laxman Dhulipala, Lars Gottesbüren, Jakub Łącki, and Vahab Mirrokni
Proceedings of the 2nd Workshop on Vector Databases (VecDB @ VLDB), 2026.
Best Paper Award
Selected for Oral Presentation
[pdf]
Tobias Rubel, Richard Wen, Guy Blelloch, Laxman Dhulipala, Lars Gottesbüren, Jakub Łącki, and Vahab Mirrokni
Proceedings of the 2nd Workshop on Vector Databases (VecDB @ VLDB), 2026.
Best Paper Award
Selected for Oral Presentation
JAG: Joint Attribute Graphs for Filtered Nearest Neighbor Search
[pdf] [arxiv]
Haike Xu, Guy Blelloch, Laxman Dhulipala, Lars Gottesbüren, Rajesh Jayaram, and Jakub Łącki
Proceedings of the 2nd Workshop on Vector Databases (VecDB @ VLDB), 2026.
Selected for Oral Presentation
[pdf] [arxiv]
Haike Xu, Guy Blelloch, Laxman Dhulipala, Lars Gottesbüren, Rajesh Jayaram, and Jakub Łącki
Proceedings of the 2nd Workshop on Vector Databases (VecDB @ VLDB), 2026.
Selected for Oral Presentation
MV-IVF: Multi-Vector Retrieval via Multi-Vector Clustering
[pdf]
Kishen N. Gowda, Laxman Dhulipala, Lars Gottesbüren, and Rajesh Jayaram
Proceedings of the 2nd Workshop on Vector Databases (VecDB @ VLDB), 2026.
[pdf]
Kishen N. Gowda, Laxman Dhulipala, Lars Gottesbüren, and Rajesh Jayaram
Proceedings of the 2nd Workshop on Vector Databases (VecDB @ VLDB), 2026.
UFO Trees: Practical and Provably-Efficient Parallel Batch-Dynamic Trees
[pdf] [arxiv] [code]
Quinten De Man, Atharva Sharma, Kishen N. Gowda, and Laxman Dhulipala
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2026.
Best Paper Nominee
[pdf] [arxiv] [code]
Quinten De Man, Atharva Sharma, Kishen N. Gowda, and Laxman Dhulipala
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2026.
Best Paper Nominee
PIM-zd-tree: A Fast Space-Partitioning Index Leveraging Processing-in-Memory
[pdf] [code]
Yiwei Zhao, Hongbo Kang, Ziyang Men, Yan Gu, Guy E. Blelloch, Laxman Dhulipala, Charles McGuffey, and Phillip B. Gibbons
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2026.
[pdf] [code]
Yiwei Zhao, Hongbo Kang, Ziyang Men, Yan Gu, Guy E. Blelloch, Laxman Dhulipala, Charles McGuffey, and Phillip B. Gibbons
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2026.
Efficiently Constructing Sparse Navigable Graphs
[pdf] [arxiv]
Alex Conway, Laxman Dhulipala, Martin Farach-Colton, Rob Johnson, Ben Landrum, Christopher Musco, Yarin Shechter, Torsten Suel, and Richard Wen
Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA), 2026.
[pdf] [arxiv]
Alex Conway, Laxman Dhulipala, Martin Farach-Colton, Rob Johnson, Ben Landrum, Christopher Musco, Yarin Shechter, Torsten Suel, and Richard Wen
Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA), 2026.
Fast and Theoretically Efficient Batch-Parallel Link-Cut Trees, Euler Tour Trees, and Treaps
[pdf]
Quinten De Man and Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2026.
[pdf]
Quinten De Man and Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2026.
Unleashing Graph Partitioning for Large-Scale Nearest Neighbor Search
[pdf] [arxiv]
Lars Gottesbüren, Laxman Dhulipala, Rajesh Jayaram, and Jakub Łącki
Proceedings of the VLDB Endowment (PVLDB), 2025.
[pdf] [arxiv]
Lars Gottesbüren, Laxman Dhulipala, Rajesh Jayaram, and Jakub Łącki
Proceedings of the VLDB Endowment (PVLDB), 2025.
PIM-tree: A Skew-resistant Index for Processing-in-Memory
[pdf]
Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey, and Phillip B. Gibbons
The VLDB Journal, 2025.
[pdf]
Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey, and Phillip B. Gibbons
The VLDB Journal, 2025.
Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism
[pdf] [arxiv]
Laxman Dhulipala, Monika Henzinger, George Z. Li, Quanquan C. Liu, A. R. Sricharan, and Leqi Zhu
Proceedings of the 33rd European Symposium on Algorithms (ESA), 2025.
[pdf] [arxiv]
Laxman Dhulipala, Monika Henzinger, George Z. Li, Quanquan C. Liu, A. R. Sricharan, and Leqi Zhu
Proceedings of the 33rd European Symposium on Algorithms (ESA), 2025.
IVF2 Index: Fusing Classic and Spatial Inverted Indices for Fast Filtered ANNS
[pdf]
Ben Landrum, Magdalen Dobson Manohar, Mazin Karjikar, and Laxman Dhulipala
Proceedings of the 1st Workshop on Vector Databases at International Conference on Machine Learning, 2025.
[pdf]
Ben Landrum, Magdalen Dobson Manohar, Mazin Karjikar, and Laxman Dhulipala
Proceedings of the 1st Workshop on Vector Databases at International Conference on Machine Learning, 2025.
Scaling Parallel Algorithms to Massive Datasets using Multi-SSD Machines
[pdf] [code]
Haohong Li, Jamshed Khan, Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2025.
[pdf] [code]
Haohong Li, Jamshed Khan, Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2025.
Fully-Dynamic Parallel Algorithms for Single-Linkage Clustering
[pdf]
Quinten De Man, Laxman Dhulipala, Kishen Gowda
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2025.
[pdf]
Quinten De Man, Laxman Dhulipala, Kishen Gowda
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2025.
Optimal Batch-Dynamic kd-trees for Processing-in-Memory with Applications
[pdf]
Yiwei Zhao, Hongbo Kang, Yan Gu, Guy E. Blelloch, Laxman Dhulipala, Charles McGuffey, Phillip B. Gibbons
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2025.
[pdf]
Yiwei Zhao, Hongbo Kang, Yan Gu, Guy E. Blelloch, Laxman Dhulipala, Charles McGuffey, Phillip B. Gibbons
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2025.
Towards Scalable and Practical Batch-Dynamic Connectivity
[arxiv] [code]
Quinten De Man, Laxman Dhulipala, Adam Karczmarz, Jakub Łącki, Julian Shun, Zhongqi Wang
Proceedings of the VLDB Endowment (PVLDB), 2025.
[arxiv] [code]
Quinten De Man, Laxman Dhulipala, Adam Karczmarz, Jakub Łącki, Julian Shun, Zhongqi Wang
Proceedings of the VLDB Endowment (PVLDB), 2025.
The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering
[arxiv] [code]
Shangdi Yu, Jessica Shi, Jamison Meindl, David Eisenstat, Xiaoen Ju, Sasan Tavakkol, Laxman Dhulipala, Jakub Łącki, Vahab Mirrokni, Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2025.
[arxiv] [code]
Shangdi Yu, Jessica Shi, Jamison Meindl, David Eisenstat, Xiaoen Ju, Sasan Tavakkol, Laxman Dhulipala, Jakub Łącki, Vahab Mirrokni, Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2025.
DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering
[pdf]
Shangdi Yu, Laxman Dhulipala, Jakub Łącki, Nikos Parotsidis
Proceedings of the SIAM International Conference on Data Mining (SDM), 2025
Best Paper Award
[pdf]
Shangdi Yu, Laxman Dhulipala, Jakub Łącki, Nikos Parotsidis
Proceedings of the SIAM International Conference on Data Mining (SDM), 2025
Best Paper Award
Techniques for Practical Parallel BFS and SSSP
[pdf]
Quinten De Man, Richard Wen, Laxman Dhulipala
Proceedings of the 1st FastCode Programming Challenge, 2025
[pdf]
Quinten De Man, Richard Wen, Laxman Dhulipala
Proceedings of the 1st FastCode Programming Challenge, 2025
Approximate Nearest Neighbor Search with Window Filters
[pdf] [arxiv]
Joshua Engels, Benjamin Landrum, Shangdi Yu, Laxman Dhulipala, and Julian Shun
Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.
[pdf] [arxiv]
Joshua Engels, Benjamin Landrum, Shangdi Yu, Laxman Dhulipala, and Julian Shun
Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.
Results of the Big ANN: NeurIPS'23 Competition
[arxiv]
Harsha Vardhan Simhadri, Martin Aumüller, Amir Ingber, Matthijs Douze, George Williams, Magdalen Dobson Manohar, Dmitry Baranchuk, Edo Liberty, Frank Liu, Ben Landrum, Mazin Karjikar, Laxman Dhulipala, et al.
Proceedings of Machine Learning Research (PMLR), NeurIPS 2023 Competitions Track, 2024.
Won the NeurIPS'23 Competition Track: Big-ANN (Filtering)
[arxiv]
Harsha Vardhan Simhadri, Martin Aumüller, Amir Ingber, Matthijs Douze, George Williams, Magdalen Dobson Manohar, Dmitry Baranchuk, Edo Liberty, Frank Liu, Ben Landrum, Mazin Karjikar, Laxman Dhulipala, et al.
Proceedings of Machine Learning Research (PMLR), NeurIPS 2023 Competitions Track, 2024.
Won the NeurIPS'23 Competition Track: Big-ANN (Filtering)
MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encoding
[arxiv]
Rajesh Jayaram, Laxman Dhulipala, Majid Hadian, Jason D Lee, Vahab Mirrokni
Conference on Neural Information Processing Systems (NeurIPS), 2024.
[arxiv]
Rajesh Jayaram, Laxman Dhulipala, Majid Hadian, Jason D Lee, Vahab Mirrokni
Conference on Neural Information Processing Systems (NeurIPS), 2024.
Efficient Centroid-Linkage Clustering
[arxiv]
MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher, Kishen N Gowda, D Ellis Hershkowitz, Rajesh Jayaram, Jakub Łącki
Conference on Neural Information Processing Systems (NeurIPS), 2024.
[arxiv]
MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher, Kishen N Gowda, D Ellis Hershkowitz, Rajesh Jayaram, Jakub Łącki
Conference on Neural Information Processing Systems (NeurIPS), 2024.
Parallel Set Cover and Hypergraph Matching via Uniform Random Sampling
[arxiv]
Laxman Dhulipala, Michael Dinitz, Jakub Łącki, Slobodan Mitrovic
Proceedings of the International Symposium on Distributed Computing (DISC 2024)
[arxiv]
Laxman Dhulipala, Michael Dinitz, Jakub Łącki, Slobodan Mitrovic
Proceedings of the International Symposium on Distributed Computing (DISC 2024)
BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers
[arxiv]
Brian Wheatman, Xiaojun Dong, Zheqi Shen, Laxman Dhulipala, Jakub Łącki, Prashant Pandey, Helen Xu
Proceedings of the VLDB Endowment, 2024.
[arxiv]
Brian Wheatman, Xiaojun Dong, Zheqi Shen, Laxman Dhulipala, Jakub Łącki, Prashant Pandey, Helen Xu
Proceedings of the VLDB Endowment, 2024.
Optimal Parallel Algorithms for Dendrogram Computation and Single-Linkage Clustering
[arxiv] [code]
Laxman Dhulipala, Xiaojun Dong, Kishen Gowda, and Yan Gu
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2024.
[arxiv] [code]
Laxman Dhulipala, Xiaojun Dong, Kishen Gowda, and Yan Gu
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2024.
It's Hard to HAC with Average Linkage!
[pdf] [arxiv]
MohammadHossein Bateni, Laxman Dhulipala, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, and Jakub Łącki
Proceedings of the 51st International Colloquium on Automata, Languages, and Programming (ICALP), 2024.
[pdf] [arxiv]
MohammadHossein Bateni, Laxman Dhulipala, Kishen N. Gowda, D. Ellis Hershkowitz, Rajesh Jayaram, and Jakub Łącki
Proceedings of the 51st International Colloquium on Automata, Languages, and Programming (ICALP), 2024.
ParlayANN: Scalable and Deterministic Parallel Graph-Based Algorithms for Approximate Nearest Neighbor Search
[arxiv] [code]
Magdalen Dobson, Zheqi Shen, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Harsha Vardhan Simhadri, and Yihan Sun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2024.
[arxiv] [code]
Magdalen Dobson, Zheqi Shen, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Harsha Vardhan Simhadri, and Yihan Sun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2024.
Parallel Integer Sort: Theory and Practice
[arxiv]
Xiaojun Dong, Laxman Dhulipala, Yan Gu, and Yihan Sun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2024.
[arxiv]
Xiaojun Dong, Laxman Dhulipala, Yan Gu, and Yihan Sun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2024.
TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs
[arxiv]
Laxman Dhulipala, Jason Lee, Jakub Łącki, and Vahab Mirrokni
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2024.
[arxiv]
Laxman Dhulipala, Jason Lee, Jakub Łącki, and Vahab Mirrokni
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2024.
Parallel Algorithms for Hierarchical Nucleus Decomposition
[arxiv]
Jessica Shi, Laxman Dhulipala, and Julian Shun
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2024.
[arxiv]
Jessica Shi, Laxman Dhulipala, and Julian Shun
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2024.
Practical Parallel Algorithms for Near-Optimal Densest Subgraphs on Massive Graphs
[arxiv]
Pattara Sukprasert, Quanquan C. Liu, Laxman Dhulipala, and Julian Shun
Proceedings of the SIAM Meeting on Algorithm Engineering and Experiments (ALENEX), 2024.
[arxiv]
Pattara Sukprasert, Quanquan C. Liu, Laxman Dhulipala, and Julian Shun
Proceedings of the SIAM Meeting on Algorithm Engineering and Experiments (ALENEX), 2024.
Fast, Parallel, and Cache-Friendly Suffix Array Construction
[pdf] [code]
Jamshed Khan, Tobias Rubel, Laxman Dhulipala, Erin K. Molloy, and Rob Patro
Workshop on Algorithms in Bioinformatics (WABI), 2023. Also in Algorithms for Molecular Biology (AMOB), 2024.
[pdf] [code]
Jamshed Khan, Tobias Rubel, Laxman Dhulipala, Erin K. Molloy, and Rob Patro
Workshop on Algorithms in Bioinformatics (WABI), 2023. Also in Algorithms for Molecular Biology (AMOB), 2024.
PIM-trie: A Skew-resistant Trie for Processing-in-Memory.
[pdf]
Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey and Phillip B. Gibbons
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2023.
[pdf]
Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey and Phillip B. Gibbons
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2023.
High-Performance and Flexible Parallel Algorithms for Semisort and Related Problems
[pdf] [arxiv]
Xiaojun Dong, Yunshu Wu, Zhongqi Wang, Laxman Dhulipala, Yan Gu, and Yihan Sun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2023.
[pdf] [arxiv]
Xiaojun Dong, Yunshu Wu, Zhongqi Wang, Laxman Dhulipala, Yan Gu, and Yihan Sun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2023.
Towards Lightweight and Automated Representation Learning System for Networks.
[arxiv]
Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala, Wenjian Yu, Jie Tang, Richard Peng, and Chi Wang
IEEE Transactions on Knowledge and Data Engineering, 2023.
[arxiv]
Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala, Wenjian Yu, Jie Tang, Richard Peng, and Chi Wang
IEEE Transactions on Knowledge and Data Engineering, 2023.
Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth
[arxiv]
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirronki, and Jessica Shi
Conference on Neural Information Processing Systems (NeurIPS), 2022.
[arxiv]
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirronki, and Jessica Shi
Conference on Neural Information Processing Systems (NeurIPS), 2022.
PIM-tree: A Skew-resistant Index for Processing-in-Memory
[arxiv]
Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey and Phillip B. Gibbons
Proceedings of the VLDB Endowment, 2022.
Best Paper Runner Up
[arxiv]
Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey and Phillip B. Gibbons
Proceedings of the VLDB Endowment, 2022.
Best Paper Runner Up
Differential Privacy from Locally Adjustable Graph Algorithms: k-Core Decomposition, Low Out-Degree Ordering, and Densest Subgraphs
[arxiv]
Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova, Jessica Shi, Julian Shun, and Shangdi Yu
Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), 2022.
[arxiv]
Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova, Jessica Shi, Julian Shun, and Shangdi Yu
Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), 2022.
ParGeo: A Library for Parallel Computational Geometry
[arxiv]
Yiqiu Wang, Rahul Yesantharao, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun
Proceedings of the European Symposium on Algorithms (ESA), 2022.
[arxiv]
Yiqiu Wang, Rahul Yesantharao, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun
Proceedings of the European Symposium on Algorithms (ESA), 2022.
Parallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems
[pdf]
Quanquan Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2022.
Best Paper Award
[pdf]
Quanquan Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2022.
Best Paper Award
Theoretically and Practically Efficient Parallel Nucleus Decomposition
[pdf] [arxiv]
Jessica Shi, Laxman Dhulipala, and Julian Shun
Proceedings of the VLDB Endowment, 2022.
[pdf] [arxiv]
Jessica Shi, Laxman Dhulipala, and Julian Shun
Proceedings of the VLDB Endowment, 2022.
PaC-trees: Supporting Parallel and Compressed Purely-Functional Collections
[pdf] [code]
Laxman Dhulipala, Guy E. Blelloch, Yan Gu, and Yihan Sun
ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2022.
[pdf] [code]
Laxman Dhulipala, Guy E. Blelloch, Yan Gu, and Yihan Sun
ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2022.
ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
[pdf] [arxiv]
Shangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, and Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2022.
[pdf] [arxiv]
Shangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, and Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2022.
POSTER: The Problem-Based Benchmark Suite (PBBS), V2
[pdf] [code]
Daniel Anderson, Guy E. Blelloch, Laxman Dhulipala, Magdalen Dobson, and Yihan Sun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2022.
[pdf] [code]
Daniel Anderson, Guy E. Blelloch, Laxman Dhulipala, Magdalen Dobson, and Yihan Sun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2022.
POSTER: ParGeo: A Library for Parallel Computational Geometry
[pdf] [code]
Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2022.
[pdf] [code]
Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun
Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2022.
Hierarchical Agglomerative Graph Clustering in Nearly Linear Time
[pdf] [arxiv]
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirronki, and Jessica Shi
Proceedings of the International Conference on Machine Learning (ICML), 2021.
[pdf] [arxiv]
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirronki, and Jessica Shi
Proceedings of the International Conference on Machine Learning (ICML), 2021.
Scalable Community Detection via Parallel Correlation Clustering
[pdf] [arxiv] [code]
Jessica Shi, Laxman Dhulipala, David Eisenstat, Jakub Łącki, and Vahab Mirrokni
Proceedings of the VLDB Endowment (PVLDB), 2021.
[pdf] [arxiv] [code]
Jessica Shi, Laxman Dhulipala, David Eisenstat, Jakub Łącki, and Vahab Mirrokni
Proceedings of the VLDB Endowment (PVLDB), 2021.
Parallel Clique Counting and Peeling Algorithms
[pdf] [arxiv] [code]
Jessica Shi, Laxman Dhulipala, and Julian Shun
Proceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA), 2021.
[pdf] [arxiv] [code]
Jessica Shi, Laxman Dhulipala, and Julian Shun
Proceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA), 2021.
The Processing-in-Memory Model
[pdf]
Hongbo Kang, Phillip B. Gibbons, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, and Charles McGuffey
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2021.
[pdf]
Hongbo Kang, Phillip B. Gibbons, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, and Charles McGuffey
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2021.
GeoGraph: A Framework for Graph Processing on Geometric Data
[pdf] [code]
Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun
ACM SIGOPS Operating Systems Review, 2021
[pdf] [code]
Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun
ACM SIGOPS Operating Systems Review, 2021
LightNE: A Lightweight Graph Processing System for Network Embedding
[pdf] [code]
Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, and Chi Wang
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
[pdf] [code]
Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, and Chi Wang
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
Parallel Index-Based Structural Graph Clustering and Its Approximation
[pdf] [arxiv] [code]
Tom Tseng, Laxman Dhulipala, and Julian Shun
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
[pdf] [arxiv] [code]
Tom Tseng, Laxman Dhulipala, and Julian Shun
Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
ConnectIt: A Framework for Static and Incremental Parallel Connectivity Algorithms
[pdf] [arxiv] [code]
Laxman Dhulipala, Changwan Hong, and Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2021.
[pdf] [arxiv] [code]
Laxman Dhulipala, Changwan Hong, and Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2021.
Parallel Batch-Dynamic k-Clique Counting
[pdf] [arxiv]
Laxman Dhulipala, Quanquan Liu, Julian Shun, and Shangdi Yu
Proceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), 2021.
[pdf] [arxiv]
Laxman Dhulipala, Quanquan Liu, Julian Shun, and Shangdi Yu
Proceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), 2021.
The Read-Only Semi-External Model
[pdf]
Guy Blelloch, Laxman Dhulipala, Phillip Gibbons, Yan Gu, Charles McGuffey, and Julian Shun
Proceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), 2021.
[pdf]
Guy Blelloch, Laxman Dhulipala, Phillip Gibbons, Yan Gu, Charles McGuffey, and Julian Shun
Proceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), 2021.
Parallel Graph Algorithms in Constant Adaptive Rounds: Theory meets Practice
[pdf] [arxiv] [Google AI Blog Post]
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, Vahab Mirrokni, and Warren Schudy
Proceedings of the VLDB Endowment (PVLDB), 2020. (To be presented at VLDB'21)
[pdf] [arxiv] [Google AI Blog Post]
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, Vahab Mirrokni, and Warren Schudy
Proceedings of the VLDB Endowment (PVLDB), 2020. (To be presented at VLDB'21)
Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs
[pdf] [arxiv]
Changwan Hong, Laxman Dhulipala, and Julian Shun
Proceedings of International Conference on Parallel Architectures and Compilation Techniques (PACT), 2020.
[pdf] [arxiv]
Changwan Hong, Laxman Dhulipala, and Julian Shun
Proceedings of International Conference on Parallel Architectures and Compilation Techniques (PACT), 2020.
Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs
[pdf] [arxiv] [code]
Laxman Dhulipala, Charles McGuffey, Hongbo Kang, Yan Gu, Guy Blelloch, Phillip Gibbons, and Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2020.
Memorable Paper Award Finalist at the Non-Volatile Memories Workshop (NVMW’20)
[pdf] [arxiv] [code]
Laxman Dhulipala, Charles McGuffey, Hongbo Kang, Yan Gu, Guy Blelloch, Phillip Gibbons, and Julian Shun
Proceedings of the VLDB Endowment (PVLDB), 2020.
Memorable Paper Award Finalist at the Non-Volatile Memories Workshop (NVMW’20)
The Graph Based Benchmark Suite (GBBS)
[pdf] [code]
Laxman Dhulipala, Jessica Shi, Tom Tseng, Guy E. Blelloch, and Julian Shun
Proceedings of the Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), 2020
[pdf] [code]
Laxman Dhulipala, Jessica Shi, Tom Tseng, Guy E. Blelloch, and Julian Shun
Proceedings of the Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), 2020
Brief Announcement: ParlayLib – A Toolkit for Parallel Algorithms on Shared-Memory Multicore Machines
[pdf] [code]
Guy E. Blelloch, Daniel Anderson, and Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2020.
[pdf] [code]
Guy E. Blelloch, Daniel Anderson, and Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2020.
Optimizing Ordered Graph Algorithms with GraphIt
[pdf] [arxiv] [code]
Yunming Zhang, Ajay Brahmakshatriya, Xinyi Chen, Laxman Dhulipala, Shoaib Kamil, Saman Amarasinghe, and Julian Shun
Proceedings of the International Symposium on Code Generation and Optimization (CGO), 2020.
[pdf] [arxiv] [code]
Yunming Zhang, Ajay Brahmakshatriya, Xinyi Chen, Laxman Dhulipala, Shoaib Kamil, Saman Amarasinghe, and Julian Shun
Proceedings of the International Symposium on Code Generation and Optimization (CGO), 2020.
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds
[pdf] [arxiv]
Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, and Xiaorui Sun
Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA), 2020.
[pdf] [arxiv]
Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, and Xiaorui Sun
Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA), 2020.
Parallel Batch-Dynamic Trees via Change Propagation
[pdf] [arxiv]
Umut Acar, Daniel Anderson, Guy Blelloch, Laxman Dhulipala, and Sam Westrick
Proceedings of the European Symposium on Algorithms (ESA), 2020.
[pdf] [arxiv]
Umut Acar, Daniel Anderson, Guy Blelloch, Laxman Dhulipala, and Sam Westrick
Proceedings of the European Symposium on Algorithms (ESA), 2020.
Near-Optimal Massively Parallel Graph Connectivity
[pdf] [arxiv]
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, and Vahab Mirrokni
Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), 2019.
[pdf] [arxiv]
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, and Vahab Mirrokni
Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), 2019.
Low-Latency Graph Streaming Using Compressed Purely-Functional Trees
[pdf] [arxiv] [code]
Laxman Dhulipala, Guy Blelloch, and Julian Shun
Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2019.
Distinguished Paper Award
[pdf] [arxiv] [code]
Laxman Dhulipala, Guy Blelloch, and Julian Shun
Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2019.
Distinguished Paper Award
Massively Parallel Computation via Remote Memory Access
[pdf] [arxiv]
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, Vahab Mirrokni, and Warren Schudy
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2019.
Invited to Special Issue
[pdf] [arxiv]
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, Vahab Mirrokni, and Warren Schudy
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2019.
Invited to Special Issue
Parallel Batch-Dynamic Graph Connectivity
[pdf] [arxiv]
Umut Acar, Daniel Anderson, Guy Blelloch, and Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2019.
[pdf] [arxiv]
Umut Acar, Daniel Anderson, Guy Blelloch, and Laxman Dhulipala
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2019.
Batch Parallel Euler-Tour Trees
[pdf] [arxiv] [code]
Thomas Tseng, Laxman Dhulipala, and Guy Blelloch
Proceedings of the SIAM Meeting on Algorithm Engineering and Experiments (ALENEX), 2019.
[pdf] [arxiv] [code]
Thomas Tseng, Laxman Dhulipala, and Guy Blelloch
Proceedings of the SIAM Meeting on Algorithm Engineering and Experiments (ALENEX), 2019.
Theoretically Efficient Parallel Algorithms Can Be Fast and Scalable
[pdf] [arxiv] [code]
Laxman Dhulipala, Guy Blelloch, and Julian Shun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2018.
Best Paper Award
Invited to Special Issue
[pdf] [arxiv] [code]
Laxman Dhulipala, Guy Blelloch, and Julian Shun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2018.
Best Paper Award
Invited to Special Issue
Julienne: A Framework for Parallel Graph Algorithms using Work-efficient Bucketing
[pdf] [code]
Laxman Dhulipala, Guy Blelloch, and Julian Shun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2017.
[pdf] [code]
Laxman Dhulipala, Guy Blelloch, and Julian Shun
Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2017.
Compressing Graphs and Indexes with Recursive Graph Bisection
[pdf] [arxiv]
Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, and Alon Shalita
Proceedings of the ACM Conference on Knowledge Discovery and Data Mining (KDD), 2016.
[pdf] [arxiv]
Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, and Alon Shalita
Proceedings of the ACM Conference on Knowledge Discovery and Data Mining (KDD), 2016.