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ORCIDMahantesh Halappanavar
Mahantesh M. Halappanavar
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2020 – today
- 2024
[j27]Sai Munikoti
, Balasubramaniam Natarajan, Mahantesh Halappanavar:
GraMeR: Graph Meta Reinforcement learning for multi-objective influence maximization. J. Parallel Distributed Comput. 192: 104900 (2024)- [j26]Karthik Somayaji N. S., Yu Wang, Malachi Schram, Ján Drgona, Mahantesh M. Halappanavar, Frank Liu, Peng Li:
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. Trans. Mach. Learn. Res. 2024 (2024) - [j25]Sai Munikoti, Deepesh Agarwal, Laya Das, Mahantesh Halappanavar, Balasubramaniam Natarajan:
Challenges and Opportunities in Deep Reinforcement Learning With Graph Neural Networks: A Comprehensive Review of Algorithms and Applications. IEEE Trans. Neural Networks Learn. Syst. 35(11): 15051-15071 (2024) - [c90]Yu Wang, Yuxuan Yin, Karthik Somayaji N. S., Ján Drgona, Malachi Schram, Mahantesh Halappanavar, Frank Liu, Peng Li:
Semi-supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach. AAAI 2024: 15698-15705 - [c89]S. M. Ferdous, Bhargav Samineni, Alex Pothen, Mahantesh Halappanavar, Bala Krishnamoorthy:
Semi-Streaming Algorithms for Weighted k-Disjoint Matchings. ESA 2024: 53:1-53:19 - [c88]Reece Neff, Mostafa Eghbali Zarch, Marco Minutoli, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Michela Becchi:
FuseIM: Fusing Probabilistic Traversals for Influence Maximization on Exascale Systems. ICS 2024: 38-49 - [c87]S. M. Ferdous, Reece Neff, Bo Peng, Salman Shuvo, Marco Minutoli, Sayak Mukherjee, Karol Kowalski, Michela Becchi, Mahantesh Halappanavar:
Picasso: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing. IPDPS 2024: 241-252 - [c86]Naw Safrin Sattar, Hao Lu, Feiyi Wang, Mahantesh Halappanavar:
Distributed Multi-GPU Community Detection on Exascale Computing Platforms. IPDPS (Workshops) 2024: 815-824 - [c85]Siddhartha Shankar Das, S. M. Ferdous, Mahantesh M. Halappanavar, Edoardo Serra, Alex Pothen:
AGS-GNN: Attribute-guided Sampling for Graph Neural Networks. KDD 2024: 538-549 - [c84]Anusha Devulapally, Mahantesh Halappanavar, Amit Puri, Vijaykrishnan Narayanan, Andres Marquez:
Using Isoefficiency as a Metric to Assess Disaggregated Memory Systems for High Performance Computing. MEMSYS 2024: 192-197 - [c83]Kasia Swirydowicz, Jesun Firoz, Joseph B. Manzano, Mahantesh Halappanavar, Stephen Thomas, Kevin J. Barker:
A Performance and Energy Study of GPU-Resident Preconditioners for Conjugate Gradient Solvers: In the Context of Existing and Novel Approaches. SBAC-PAD 2024: 70-80 - [c82]Michael Mandulak, Sayan Ghosh, S. M. Ferdous, Mahantesh Halappanavar, George M. Slota:
Efficient Weighted Graph Matching on GPUs. SC 2024: 18 - [c81]S. M. Ferdous, Alex Pothen, Mahantesh Halappanavar:
Streaming Matching and Edge Cover in Practice. SEA 2024: 12:1-12:22 - [i41]S. M. Ferdous, Reece Neff, Bo Peng, Salman Shuvo, Marco Minutoli, Sayak Mukherjee, Karol Kowalski, Michela Becchi, Mahantesh Halappanavar:
\texttt{Picasso}: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing. CoRR abs/2401.06713 (2024) - [i40]Bhargav Samineni, S. M. Ferdous, Mahantesh Halappanavar, Bala Krishnamoorthy:
Approximate Bipartite b-Matching using Multiplicative Auction. CoRR abs/2403.05781 (2024) - [i39]Kostiantyn Lyman, Rounak Meyur, Bala Krishnamoorthy, Mahantesh Halappanavar:
Structural Validation Of Synthetic Power Distribution Networks Using The Multiscale Flat Norm. CoRR abs/2403.12334 (2024) - [i38]Fabiana Ferracina, Bala Krishnamoorthy, Mahantesh Halappanavar, Shengwei Hu, Vidyasagar Sathuvalli:
Predictive Analytics of Varieties of Potatoes. CoRR abs/2404.03701 (2024) - [i37]Siddhartha Shankar Das, S. M. Ferdous, Mahantesh M. Halappanavar, Edoardo Serra, Alex Pothen:
AGS-GNN: Attribute-guided Sampling for Graph Neural Networks. CoRR abs/2405.15218 (2024) - [i36]Hung Phan, Anurag Acharya, Sarthak Chaturvedi, Shivam Sharma, Mike Parker, Dan Nally, Ali Jannesari, Karl Pazdernik, Mahantesh Halappanavar, Sai Munikoti, Sameera Horawalavithana:
RAG vs. Long Context: Examining Frontier Large Language Models for Environmental Review Document Comprehension. CoRR abs/2407.07321 (2024) - [i35]Reet Barik, Wade Cappa, S. M. Ferdous, Marco Minutoli, Mahantesh Halappanavar, Ananth Kalyanaraman:
GreediRIS: Scalable Influence Maximization using Distributed Streaming Maximum Cover. CoRR abs/2408.10982 (2024) - [i34]Md Taufique Hussain, Mahantesh Halappanavar, Samrat Chatterjee, Filippo Radicchi, Santo Fortunato, Ariful Azad:
Parallel Algorithms for Median Consensus Clustering in Complex Networks. CoRR abs/2408.11331 (2024) - [i33]Rounak Meyur, Hung Phan, Sridevi Wagle, Jan Strube, Mahantesh Halappanavar, Sameera Horawalavithana, Anurag Acharya, Sai Munikoti:
PermitQA: A Benchmark for Retrieval Augmented Generation in Wind Siting and Permitting domain. CoRR abs/2408.11800 (2024) - [i32]Fabiana Ferracina, Payton Beeler, Mahantesh Halappanavar, Bala Krishnamoorthy, Marco Minutoli, Laura Fierce:
Learning to Simulate Aerosol Dynamics with Graph Neural Networks. CoRR abs/2409.13861 (2024) - [i31]Reet Barik, Marco Minutoli, Mahantesh Halappanavar, Ananth Kalyanaraman:
An Integrated Epidemic Simulation Workflow for Submodular Intervention Strategies. CoRR abs/2411.05243 (2024) - [i30]Caleb Stam, Emily Saldanha, Mahantesh Halappanavar, Anurag Acharya:
DISHONEST: Dissecting misInformation Spread using Homogeneous sOcial NEtworks and Semantic Topic classification. CoRR abs/2412.09578 (2024) - 2023
- [c80]Gopikrishnan Raveendran Nair, Han-Sok Suh, Mahantesh Halappanavar, Frank Liu, Jae-sun Seo, Yu Cao:
FPGA Acceleration of GCN in Light of the Symmetry of Graph Adjacency Matrix. DATE 2023: 1-6 - [c79]Rounak Meyur, Kostiantyn Lyman, Bala Krishnamoorthy, Mahantesh Halappanavar:
Structural Validation of Synthetic Power Distribution Networks Using the Multiscale Flat Norm. ICCS (4) 2023: 55-69 - [c78]Buddhika Nettasinghe, Samrat Chatterjee, Ramakrishna Tipireddy, Mahantesh M. Halappanavar:
Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains. ICML 2023: 25890-25903 - [c77]Katarzyna Borowiec, Dan Lu, Vikas Chandan, Samrat Chatterjee, Pradeep Ramuhalli, Ramakrishna Tipireddy, Mahantesh Halappanavar, Frank Liu:
Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning. ICMLA 2023: 994-999 - [c76]Luis de la Torre, Mahantesh Halappanavar:
Scaling Optimal Allocation of Cloud Resources Using Lagrange Relaxation. JSSPP 2023: 173-192 - [c75]Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti:
Faster approximate subgraph counts with privacy. NeurIPS 2023 - [c74]Pasqua D'Ambra, Fabio Durastante, S. M. Ferdous, Salvatore Filippone, Mahantesh Halappanavar, Alex Pothen:
AMG Preconditioners based on Parallel Hybrid Coarsening and Multi-objective Graph Matching. PDP 2023: 59-67 - [c73]Lizhi Xiang, Arif M. Khan, S. M. Ferdous, Aravind Sukumaran-Rajam, Mahantesh Halappanavar:
cuAlign: Scalable Network Alignment on GPU Accelerators. SC Workshops 2023: 747-755 - [i29]Ashutosh Dutta, Samrat Chatterjee, Arnab Bhattacharya, Mahantesh Halappanavar:
Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties. CoRR abs/2302.01595 (2023) - [i28]Maruti K. Mudunuru, James A. Ang, Mahantesh Halappanavar, Simon D. Hammond, Maya B. Gokhale, James C. Hoe, Tushar Krishna, Sarat Sreepathi, Matthew R. Norman, Ivy Bo Peng, Philip W. Jones:
Perspectives on AI Architectures and Co-design for Earth System Predictability. CoRR abs/2304.03748 (2023) - [i27]Laya Das, Sai Munikoti, Mahantesh Halappanavar:
There is more to graphs than meets the eye: Learning universal features with self-supervision. CoRR abs/2305.19871 (2023) - [i26]Karthik Somayaji N. S., Yu Wang, Malachi Schram, Ján Drgona, Mahantesh Halappanavar, Frank Liu, Peng Li:
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. CoRR abs/2308.13011 (2023) - [i25]Yu Wang, Yuxuan Yin, Karthik Somayaji Nanjangud Suryanarayana, Ján Drgona, Malachi Schram, Mahantesh Halappanavar, Frank Liu, Peng Li:
Semi-Supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach. CoRR abs/2310.13110 (2023) - [i24]S. M. Ferdous, Bhargav Samineni, Alex Pothen, Mahantesh Halappanavar, Bala Krishnamoorthy:
Streaming Algorithms for Weighted k-Disjoint Matchings. CoRR abs/2311.02073 (2023) - [i23]Wenceslao Shaw-Cortez, Ján Drgona, Draguna L. Vrabie, Mahantesh Halappanavar:
Robust Differentiable Predictive Control with Safety Guarantees: A Predictive Safety Filter Approach. CoRR abs/2311.08496 (2023) - [i22]Reece Neff, Mostafa Eghbali Zarch, Marco Minutoli, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Michela Becchi:
Fused Breadth-First Probabilistic Traversals on Distributed GPU Systems. CoRR abs/2311.10201 (2023) - 2022
- [j24]Xu T. Liu, Andrew Lumsdaine, Mahantesh Halappanavar, Kevin J. Barker, Assefaw Hadish Gebremedhin:
Direction-optimizing Label Propagation Framework for Structure Detection in Graphs: Design, Implementation, and Experimental Analysis. ACM J. Exp. Algorithmics 27: 1.12:1-1.12:31 (2022) - [j23]Nitin Gawande, Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman:
Towards scaling community detection on distributed-memory heterogeneous systems. Parallel Comput. 111: 102898 (2022) - [j22]Sayan Ghosh, Nathan R. Tallent, Mahantesh Halappanavar:
Characterizing Performance of Graph Neighborhood Communication Patterns. IEEE Trans. Parallel Distributed Syst. 33(4): 915-928 (2022) - [c72]Xinyu Chen, Marco Minutoli, Jiannan Tian, Mahantesh Halappanavar, Ananth Kalyanaraman, Dingwen Tao:
HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures. PACT 2022: 412-425 - [c71]Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao:
Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification. AAAI 2022: 8370-8377 - [c70]Siddhartha Shankar Das, Mahantesh Halappanavar, Antonino Tumeo, Edoardo Serra, Alex Pothen, Ehab Al-Shaer:
VWC-BERT: Scaling Vulnerability-Weakness-Exploit Mapping on Modern AI Accelerators. IEEE Big Data 2022: 1224-1229 - [c69]Wenceslao Shaw-Cortez, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. CDC 2022: 932-938 - [c68]Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Neural Lyapunov Differentiable Predictive Control. CDC 2022: 2097-2104 - [c67]Reet Barik, Marco Minutoli, Mahantesh Halappanavar, Ananth Kalyanaraman:
IMpart: A Partitioning-based Parallel Approach to Accelerate Influence Maximization. HIPC 2022: 125-134 - [c66]Prathyush Sambaturu, Marco Minutoli, Mahantesh Halappanavar, Ananth Kalyanaraman, Anil Vullikanti:
Scalable and Memory-Efficient Algorithms for Controlling Networked Epidemic Processes Using Multiplicative Weights Update Method. IJCAI 2022: 5164-5170 - [i21]Ján Drgona, Sayak Mukherjee, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Learning Stochastic Parametric Differentiable Predictive Control Policies. CoRR abs/2203.01447 (2022) - [i20]Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Neural Lyapunov Differentiable Predictive Control. CoRR abs/2205.10728 (2022) - [i19]Sai Munikoti, Balasubramaniam Natarajan, Mahantesh Halappanavar:
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization. CoRR abs/2205.14834 (2022) - [i18]Sai Munikoti, Deepesh Agarwal, Laya Das, Mahantesh Halappanavar, Balasubramaniam Natarajan:
Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications. CoRR abs/2206.07922 (2022) - [i17]Xinyu Chen, Marco Minutoli, Jiannan Tian, Mahantesh Halappanavar, Ananth Kalyanaraman, Dingwen Tao:
HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures. CoRR abs/2208.00613 (2022) - [i16]Wenceslao Shaw-Cortez, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. CoRR abs/2208.02319 (2022) - [i15]Buddhika Nettasinghe, Samrat Chatterjee, Ramakrishna Tipireddy, Mahantesh Halappanavar:
Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains. CoRR abs/2210.02271 (2022) - 2021
- [j21]Tanveer Hossain Bhuiyan, Hugh R. Medal, Apurba K. Nandi, Mahantesh Halappanavar:
Risk-averse bi-level stochastic network interdiction model for cyber-security risk management. Int. J. Crit. Infrastructure Prot. 32: 100408 (2021) - [j20]Seher Acer, Ariful Azad, Erik G. Boman, Aydin Buluç, Karen D. Devine, S. M. Ferdous, Nitin Gawande, Sayan Ghosh, Mahantesh Halappanavar, Ananth Kalyanaraman, Arif Khan, Marco Minutoli, Alex Pothen, Sivasankaran Rajamanickam, Oguz Selvitopi, Nathan R. Tallent, Antonino Tumeo:
EXAGRAPH: Graph and combinatorial methods for enabling exascale applications. Int. J. High Perform. Comput. Appl. 35(6): 553-571 (2021) - [c65]S. M. Ferdous, Alex Pothen, Arif Khan, Ajay Panyala, Mahantesh Halappanavar:
A Parallel Approximation Algorithm for Maximizing Submodular b-Matching. ACDA 2021: 45-56 - [c64]Milan Jain, Khushboo Gupta, Arun V. Sathanur, Vikas Chandan, Mahantesh Halappanavar:
Transfer-Learnt Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data. ACC 2021: 2887-2894 - [c63]Mahantesh Halappanavar, Marco Minutoli, Sayan Ghosh:
Graph analytics in the exascale era. CF 2021: 209 - [c62]Siddhartha Shankar Das, Edoardo Serra, Mahantesh Halappanavar, Alex Pothen, Ehab Al-Shaer:
V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities. DSAA 2021: 1-12 - [c61]Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar:
On the Stochastic Stability of Deep Markov Models. NeurIPS 2021: 24033-24047 - [c60]Sayan Ghosh, Nathan R. Tallent, Marco Minutoli, Mahantesh Halappanavar, Ramesh Peri, Ananth Kalyanaraman:
Single-node partitioned-memory for huge graph analytics: cost and performance trade-offs. SC 2021: 55 - [c59]Lizhi Xiang, Arif Khan, Edoardo Serra, Mahantesh Halappanavar, Aravind Sukumaran-Rajam:
cuTS: scaling subgraph isomorphism on distributed multi-GPU systems using trie based data structure. SC 2021: 69 - [c58]Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao:
Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification. CSSL 2021: 118-133 - [i14]Siddhartha Shankar Das, Edoardo Serra, Mahantesh Halappanavar, Alex Pothen, Ehab Al-Shaer:
V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities. CoRR abs/2102.11498 (2021) - [i13]S. M. Ferdous, Alex Pothen, Arif Khan, Ajay Panyala, Mahantesh Halappanavar:
A Parallel Approximation Algorithm for Maximizing Submodular b-Matching. CoRR abs/2107.05793 (2021) - [i12]Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar:
On the Stochastic Stability of Deep Markov Models. CoRR abs/2111.04601 (2021) - [i11]Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao:
Gradient-based Novelty Detection Boosted by Self-supervised Binary Classification. CoRR abs/2112.09815 (2021) - 2020
- [j19]Antonino Tumeo, Fabrizio Petrini, John Feo, Mahantesh Halappanavar:
Introduction to the TOPC Special Issue on Innovations in Systems for Irregular Applications, Part 1. ACM Trans. Parallel Comput. 7(1): 1:1-1:2 (2020) - [j18]Antonino Tumeo, Fabrizio Petrini, John Feo, Mahantesh Halappanavar:
Introduction to the TOPC Special Issue on Innovations in Systems for Irregular Applications, Part 2. ACM Trans. Parallel Comput. 7(4): 23:1-23:2 (2020) - [c57]Xu T. Liu, Mahantesh Halappanavar, Kevin J. Barker, Andrew Lumsdaine, Assefaw H. Gebremedhin:
Direction-optimizing label propagation and its application to community detection. CF 2020: 192-201 - [c56]Sayan Ghosh, Mahantesh Halappanavar:
TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure. HPEC 2020: 1-6 - [c55]Marco Minutoli, Maurizio Drocco, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman:
cuRipples: influence maximization on multi-GPU systems. ICS 2020: 12:1-12:11 - [c54]Reet Barik, Marco Minutoli, Mahantesh Halappanavar, Nathan R. Tallent, Ananth Kalyanaraman:
Vertex Reordering for Real-World Graphs and Applications: An Empirical Evaluation. IISWC 2020: 240-251 - [c53]Scott McMillan, Manoj Kumar, Danai Koutra, Mahantesh Halappanavar, Tim Mattson, Antonino Tumeo:
Message from the workshop chairs. IPDPS Workshops 2020: 199-200 - [c52]Marco Minutoli, Prathyush Sambaturu, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Anil Vullikanti:
Preempt: scalable epidemic interventions using submodular optimization on multi-GPU systems. SC 2020: 55
2010 – 2019
- 2019
- [j17]Sinan G. Aksoy, Emilie Purvine, Eduardo Cotilla Sanchez, Mahantesh Halappanavar:
A generative graph model for electrical infrastructure networks. J. Complex Networks 7(1): 128-162 (2019) - [j16]Florin Dobrian, Mahantesh Halappanavar, Alex Pothen, Ahmed Al-Herz:
A 2/3-Approximation Algorithm for Vertex Weighted Matching in Bipartite Graphs. SIAM J. Sci. Comput. 41(1): A566-A591 (2019) - [c51]Marco Minutoli, Mahantesh Halappanavar, Ananth Kalyanaraman, Arun V. Sathanur, Ryan S. McClure, Jason E. McDermott:
Fast and Scalable Implementations of Influence Maximization Algorithms. CLUSTER 2019: 1-12 - [c50]Arif M. Khan, Mahantesh Halappanavar, Tobias Hagge, Karol Kowalski, Alex Pothen, Sriram Krishnamoorthy:
Mapping Arbitrarily Sparse Two-Body Interactions on One-Dimensional Quantum Circuits. HiPC 2019: 52-62 - [c49]Xu Liu, Jesun Sahariar Firoz, Marcin Zalewski, Mahantesh Halappanavar, Kevin J. Barker, Andrew Lumsdaine, Assefaw H. Gebremedhin:
Distributed Direction-Optimizing Label Propagation for Community Detection. HPEC 2019: 1-6 - [c48]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman:
Scaling and Quality of Modularity Optimization Methods for Graph Clustering. HPEC 2019: 1-6 - [c47]Sayan Ghosh, Mahantesh Halappanavar, Ananth Kalyanaraman, Arif Khan, Assefaw H. Gebremedhin:
Exploring MPI Communication Models for Graph Applications Using Graph Matching as a Case Study. IPDPS 2019: 761-770 - 2018
- [j15]Craig Bakker, Mahantesh Halappanavar, Arun V. Sathanur:
Dynamic graphs, community detection, and Riemannian geometry. Appl. Netw. Sci. 3(1): 3:1-3:30 (2018) - [j14]Ananth Kalyanaraman, Mahantesh Halappanavar:
Guest Editorial: Advances in Parallel Graph Processing: Algorithms, Architectures, and Application Frameworks. IEEE Trans. Multi Scale Comput. Syst. 4(3): 188-189 (2018) - [c46]Ryan D. Friese, Nathan R. Tallent, Malachi Schram, Mahantesh Halappanavar, Kevin J. Barker:
Optimizing Distributed Data-Intensive Workflows. CLUSTER 2018: 279-289 - [c45]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Assefaw H. Gebremedhin:
Scalable Distributed Memory Community Detection Using Vite. HPEC 2018: 1-7 - [c44]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Hao Lu, Daniel G. Chavarría-Miranda, Arif Khan, Assefaw Hadish Gebremedhin:
Distributed Louvain Algorithm for Graph Community Detection. IPDPS 2018: 885-895 - [c43]Antonino Tumeo, Mahantesh Halappanavar, John Feo, Assefaw Hadish Gebremedhin, Abhinav Vishnu:
Introduction to GraML 2018. IPDPS Workshops 2018: 1166-1167 - [c42]Tanveer Hossain Bhuiyan, Mahantesh Halappanavar, Ryan D. Friese, Hugh R. Medal, Luis de la Torre, Arun V. Sathanur, Nathan R. Tallent:
Stochastic Programming Approach for Resource Selection Under Demand Uncertainty. JSSPP 2018: 107-126 - [c41]Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Assefaw H. Gebremedhin:
MiniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems. PMBS@SC 2018: 51-56 - [c40]Arif Khan, Krzysztof Choromanski, Alex Pothen, S. M. Ferdous, Mahantesh Halappanavar, Antonino Tumeo:
Adaptive anonymization of data using b-edge cover. SC 2018: 59:1-59:11 - [p1]Arun V. Sathanur, Mahantesh Halappanavar, Yi Shi, Yalin E. Sagduyu:
Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks. Social Network Based Big Data Analysis and Applications 2018: 123-142 - [i10]Florin Dobrian, Mahantesh Halappanavar, Alex Pothen, Ahmed Al-Herz:
A 2/3-Approximation Algorithm for Vertex-weighted Matching in Bipartite Graphs. CoRR abs/1804.08016 (2018) - 2017
- [j13]Ajay Panyala, Daniel G. Chavarría-Miranda, Joseph B. Manzano, Antonino Tumeo, Mahantesh Halappanavar:
Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture. J. Parallel Distributed Comput. 104: 234-251 (2017) - [j12]Emilie Purvine, Eduardo Cotilla Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang:
Comparative study of clustering techniques for real-time dynamic model reduction. Stat. Anal. Data Min. 10(5): 263-276 (2017) - [j11]Yu Hong Yeung, Alex Pothen, Mahantesh Halappanavar, Zhenyu Huang:
AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids. SIAM J. Sci. Comput. 39(5) (2017) - [j10]Hao Lu, Mahantesh Halappanavar, Daniel G. Chavarría-Miranda, Assefaw Hadish Gebremedhin, Ajay Panyala, Ananth Kalyanaraman:
Algorithms for Balanced Graph Colorings with Applications in Parallel Computing. IEEE Trans. Parallel Distributed Syst. 28(5): 1240-1256 (2017) - [c39]Ajay Panyala, Omer Subasi, Mahantesh Halappanavar, Ananth Kalyanaraman, Daniel G. Chavarría-Miranda, Sriram Krishnamoorthy:
Approximate Computing Techniques for Iterative Graph Algorithms. HiPC 2017: 23-32 - [c38]Mahantesh Halappanavar, Hao Lu, Ananth Kalyanaraman, Antonino Tumeo:
Scalable static and dynamic community detection using Grappolo. HPEC 2017: 1-6 - [c37]Sudip Saha, Anil Vullikanti, Mahantesh Halappanavar:
FlipNet: Modeling Covert and Persistent Attacks on Networked Resources. ICDCS 2017: 2444-2451 - [c36]Md. Naim, Fredrik Manne, Mahantesh Halappanavar, Antonino Tumeo:
Community Detection on the GPU. IPDPS 2017: 625-634 - [c35]Antonino Tumeo, Mahantesh Halappanavar, John Feo:
Introduction to GraML Workshop. IPDPS Workshops 2017: 1529-1530 - [c34]Ryan D. Friese, Mahantesh Halappanavar, Arun V. Sathanur, Malachi Schram, Darren J. Kerbyson, Luis de la Torre:
Towards Efficient Resource Allocation for Distributed Workflows Under Demand Uncertainties. JSSPP 2017: 103-121 - [e1]Srinivas Alum, Ananth Kalyanaraman, Bora Uçar, Kishore Kothapalli, Mahantesh Halappanavar, Kamesh Madduri, Madhu Govindaraju, Yinglong Xia, Sushil K. Prasad, Martina Barnas, Ashish Sureka, Pankesh Patel, Vikas Saxena, Sanjay Goel:
Tenth International Conference on Contemporary Computing, IC3 2017, Noida, India, August 10-12, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-3077-8 [contents] - [i9]Yu Hong Yeung, Alex Pothen, Mahantesh Halappanavar, Zhenyu Huang:
AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids. CoRR abs/1706.03147 (2017) - [i8]Arun V. Sathanur, Mahantesh Halappanavar, Yi Shi, Yalin E. Sagduyu:
Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks. CoRR abs/1707.05287 (2017) - [i7]Sinan G. Aksoy, Emilie Purvine, Eduardo Cotilla Sanchez, Mahantesh Halappanavar:
A generative graph model for electrical infrastructure networks. CoRR abs/1711.11098 (2017) - 2016
- [j9]Ananth Kalyanaraman, Mahantesh Halappanavar, Daniel G. Chavarría-Miranda, Hao Lu, Karthi Duraisamy, Partha Pratim Pande:
Fast Uncovering of Graph Communities on a Chip: Toward Scalable Community Detection on Multicore and Manycore Platforms. Found. Trends Electron. Des. Autom. 10(3): 145-247 (2016) - [j8]Arif M. Khan, Alex Pothen, Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Fredrik Manne, Mahantesh Halappanavar, Pradeep Dubey:
Efficient Approximation Algorithms for Weighted b-Matching. SIAM J. Sci. Comput. 38(5) (2016) - [c33]Usman Rauf, Fida Gillani, Ehab Al-Shaer, Mahantesh Halappanavar, Samrat Chatterjee, Christopher S. Oehmen:
Formal Approach for Resilient Reachability based on End-System Route Agility. MTD@CCS 2016: 117-127 - [c32]Mahantesh Halappanavar, Arun V. Sathanur, Apurba K. Nandi:
Accelerating the mining of influential nodes in complex networks through community detection. Conf. Computing Frontiers 2016: 64-71 - [c31]Nathan R. Tallent, Kevin J. Barker, Daniel G. Chavarría-Miranda, Antonino Tumeo, Mahantesh Halappanavar, Andrès Márquez, Darren J. Kerbyson, Adolfy Hoisie:
Modeling the Impact of Silicon Photonics on Graph Analytics. NAS 2016: 1-11 - [c30]Arif M. Khan, Alex Pothen, Md. Mostofa Ali Patwary, Mahantesh Halappanavar, Nadathur Rajagopalan Satish, Narayanan Sundaram, Pradeep Dubey:
Designing scalable b-Matching algorithms on distributed memory multiprocessors by approximation. SC 2016: 773-783 - [c29]Fredrik Manne, Md. Naim, Håkon Lerring, Mahantesh Halappanavar:
On Stable Marriages and Greedy Matchings. CSC 2016: 92-101 - [c28]Arun V. Sathanur, Mahantesh Halappanavar:
Influence Maximization on Complex Networks with Intrinsic Nodal Activation. SocInfo (2) 2016: 133-141 - 2015
- [j7]Mahantesh Halappanavar, Alex Pothen, Ariful Azad, Fredrik Manne, Johannes Langguth, Arif M. Khan:
Codesign Lessons Learned from Implementing Graph Matching on Multithreaded Architectures. Computer 48(8): 46-55 (2015) - [j6]Sanjukta Bhowmick, Tzu-Yi Chen, Mahantesh Halappanavar:
A new augmentation based algorithm for extracting maximal chordal subgraphs. J. Parallel Distributed Comput. 76: 132-144 (2015) - [j5]Hao Lu, Mahantesh Halappanavar, Ananth Kalyanaraman:
Parallel heuristics for scalable community detection. Parallel Comput. 47: 19-37 (2015) - [c27]Daniel G. Chavarría-Miranda, Ajay Panyala, Mahantesh Halappanavar, Joseph B. Manzano, Antonino Tumeo:
Optimizing irregular applications for energy and performance on the Tilera many-core architecture. Conf. Computing Frontiers 2015: 12:1-12:8 - [c26]Md. Naim, Fredrik Manne, Mahantesh Halappanavar, Antonino Tumeo, Johannes Langguth:
Optimizing Approximate Weighted Matching on Nvidia Kepler K40. HiPC 2015: 105-114 - [c25]Hao Lu, Mahantesh Halappanavar, Daniel G. Chavarría-Miranda, Assefaw Hadish Gebremedhin, Ananth Kalyanaraman:
Balanced Coloring for Parallel Computing Applications. IPDPS 2015: 7-16 - [c24]Daniel G. Chavarría-Miranda, Mahantesh Halappanavar, Sriram Krishnamoorthy, Joseph B. Manzano, Abhinav Vishnu, Adolfy Hoisie:
On the Impact of Execution Models: A Case Study in Computational Chemistry. IPDPS Workshops 2015: 255-264 - [c23]Mahantesh Halappanavar, Malachi Schram, Luis de la Torre, Kevin J. Barker, Nathan R. Tallent, Darren J. Kerbyson:
Towards efficient scheduling of data intensive high energy physics workflows. WORKS@SC 2015: 3:1-3:9 - [i6]Emilie Hogan, Eduardo Cotilla Sanchez, Mahantesh Halappanavar, Zhenyu Huang, Guang Lin, Shuai Lu, Shaobu Wang:
Comparative Studies of Clustering Techniques for Real-Time Dynamic Model Reduction. CoRR abs/1501.00943 (2015) - [i5]Mahantesh Halappanavar, Eduardo Cotilla Sanchez, Emilie Hogan, Daniel Duncan, Zhenyu (Henry) Huang, Paul D. H. Hines:
A Network-of-Networks Model for Electrical Infrastructure Networks. CoRR abs/1512.01436 (2015) - 2014
- [j4]Johannes Langguth, Ariful Azad, Mahantesh Halappanavar, Fredrik Manne:
On parallel push-relabel based algorithms for bipartite maximum matching. Parallel Comput. 40(7): 289-308 (2014) - [c22]Daniel G. Chavarría-Miranda, Mahantesh Halappanavar, Ananth Kalyanaraman:
Scaling graph community detection on the Tilera many-core architecture. HiPC 2014: 1-11 - [c21]Fredrik Manne, Mahantesh Halappanavar:
New Effective Multithreaded Matching Algorithms. IPDPS 2014: 519-528 - [c20]Hao Lu, Mahantesh Halappanavar, Ananth Kalyanaraman, Sutanay Choudhury:
Parallel Heuristics for Scalable Community Detection. IPDPS Workshops 2014: 1374-1385 - [i4]Hao Lu, Mahantesh Halappanavar, Ananth Kalyanaraman:
Parallel Heuristics for Scalable Community Detection. CoRR abs/1410.1237 (2014) - 2013
- [j3]Nawab Ali, Sriram Krishnamoorthy, Mahantesh Halappanavar, Jeff Daily:
Multi-Fault Tolerance for Cartesian Data Distributions. Int. J. Parallel Program. 41(3): 469-493 (2013) - [c19]Emilie Hogan, John R. Johnson, Mahantesh Halappanavar:
Graph coarsening for path finding in cybersecurity graphs. CSIIRW 2013: 7 - [c18]Mahantesh Halappanavar, Sutanay Choudhury, Emilie Hogan, Peter Hui, John R. Johnson, Indrajit Ray, Lawrence B. Holder:
Towards a network-of-networks framework for cyber security. ISI 2013: 106-108 - [c17]Emilie Hogan, John R. Johnson, Mahantesh Halappanavar, Chaomei Lo:
Graph analytics for signature discovery. ISI 2013: 315-320 - [c16]Emilie Hogan, Eduardo Cotilla Sanchez, Mahantesh Halappanavar, Shaobu Wang, Patrick Mackey, Paul Hines, Zhenyu Huang:
Towards effective clustering techniques for the analysis of electric power grids. HiPCNA-PG@SC 2013: 1:1-1:8 - [i3]Mahantesh Halappanavar, Sutanay Choudhury, Emilie Hogan, Peter Hui, John R. Johnson, Indrajit Ray, Lawrence B. Holder:
Towards a Networks-of-Networks Framework for Cyber Security. CoRR abs/1304.6761 (2013) - 2012
- [j2]Mahantesh Halappanavar, John Feo, Oreste Villa, Antonino Tumeo, Alex Pothen:
Approximate weighted matching on emerging manycore and multithreaded architectures. Int. J. High Perform. Comput. Appl. 26(4): 413-430 (2012) - [j1]Ümit V. Çatalyürek, John Feo, Assefaw Hadish Gebremedhin, Mahantesh Halappanavar, Alex Pothen:
Graph coloring algorithms for multi-core and massively multithreaded architectures. Parallel Comput. 38(10-11): 576-594 (2012) - [c15]Chad Scherrer, Mahantesh Halappanavar, Ambuj Tewari, David Haglin:
Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems. ICML 2012 - [c14]Mahantesh Halappanavar, John Feo, Kathryn Dempsey, Hesham H. Ali, Sanjukta Bhowmick:
A Novel Multithreaded Algorithm for Extracting Maximal Chordal Subgraphs. ICPP 2012: 58-67 - [c13]Ariful Azad, Mahantesh Halappanavar, Sivasankaran Rajamanickam, Erik G. Boman, Arif M. Khan, Alex Pothen:
Multithreaded Algorithms for Maxmum Matching in Bipartite Graphs. IPDPS 2012: 860-872 - [c12]Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar, David Haglin:
Feature Clustering for Accelerating Parallel Coordinate Descent. NIPS 2012: 28-36 - [c11]Arif M. Khan, David F. Gleich, Alex Pothen, Mahantesh Halappanavar:
A multithreaded algorithm for network alignment via approximate matching. SC 2012: 64 - [c10]Mahantesh Halappanavar, Yousu Chen, Robert Adolf, David Haglin, Zhenyu Huang, Mark Rice:
Towards Efficient N-x Contingency Selection Using Group betweenness Centrality. SC Companion 2012: 273-282 - [i2]Ümit V. Çatalyürek, John Feo, Assefaw Hadish Gebremedhin, Mahantesh Halappanavar, Alex Pothen:
Graph Coloring Algorithms for Muti-core and Massively Multithreaded Architectures. CoRR abs/1205.3809 (2012) - [i1]Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar, David J. Haglin:
Feature Clustering for Accelerating Parallel Coordinate Descent. CoRR abs/1212.4174 (2012) - 2011
- [c9]Nawab Ali, Sriram Krishnamoorthy, Mahantesh Halappanavar, Jeff Daily:
Tolerating correlated failures for generalized Cartesian distributions via bipartite matching. Conf. Computing Frontiers 2011: 36 - [c8]Ümit V. Çatalyürek, Florin Dobrian, Assefaw Hadish Gebremedhin, Mahantesh Halappanavar, Alex Pothen:
Distributed-Memory Parallel Algorithms for Matching and Coloring. IPDPS Workshops 2011: 1971-1980 - [c7]Robert Adolf, David Haglin, Mahantesh Halappanavar, Yousu Chen, Zhenyu Huang:
Techniques for Improving Filters in Power Grid Contingency Analysis. MLDM 2011: 599-611 - [c6]Ariful Azad, Mahantesh Halappanavar, Florin Dobrian, Alex Pothen:
Computing maximum matching in parallel on bipartite graphs: worth the effort? IA3@SC 2011: 11-14
2000 – 2009
- 2009
- [b1]Mahantesh Halappanavar:
Algorithms for Vertex-Weighted Matching in Graphs. Old Dominion University, Norfolk, Virginia, USA, 2009 - 2008
- [c5]Mahantesh Halappanavar, Amit Kumar, Ravi Mukkamala, Mohammad Zubair:
Efficient Parallel Implementations of Binomial Tree Option Price Valuation. PDCCS 2008: 74-81 - [c4]Mahantesh Halappanavar, John-Paul Robinson, Enis Afgan, Mary Fran Yafchak, Purushotham V. Bangalore:
A common application platform for the SURAgrid (CAP). Mardi Gras Conference 2008: 41 - 2003
- [c3]Mahantesh Halappanavar, Ravi Mukkamala:
ECPV: Efficient Certificate Path Validation in Public-key Infrastructure. DBSec 2003: 215-228 - 2002
- [c2]Ravi Mukkamala, Satyam Das, Mahantesh Halappanavar:
Recertification: A Technique to Improve Services in PKI. DBSec 2002: 259-270 - [c1]Somasekhar Vemulapalli, Mahantesh Halappanavar, Ravi Mukkamala:
Security in Distributed Digital Libraries: Issues and Challenges . ICPP Workshops 2002: 480-486
Coauthor Index
Assefaw Hadish Gebremedhin
aka: Assefaw H. Gebremedhin
aka: Assefaw H. Gebremedhin
Anantharaman Kalyanaraman
aka: Ananth Kalyanaraman
aka: Ananth Kalyanaraman
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