Mahantesh Halappanavar

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 102

Top Venues

Publications

Naw Safrin Sattar, Hao Lu, Feiyi Wang, Mahantesh Halappanavar
Distributed Multi-GPU Community Detection on Exascale Computing Platforms. IPDPS (Workshops) (2024)
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)
Kostiantyn Lyman, Rounak Meyur, Bala Krishnamoorthy, Mahantesh Halappanavar
Structural Validation Of Synthetic Power Distribution Networks Using The Multiscale Flat Norm. CoRR (2024)
S. M. Ferdous, Alex Pothen, Mahantesh Halappanavar
Streaming Matching and Edge Cover in Practice. SEA (2024)
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 (2024)
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)
Fabiana Ferracina, Bala Krishnamoorthy, Mahantesh Halappanavar, Shengwei Hu, Vidyasagar Sathuvalli
Predictive Analytics of Varieties of Potatoes. CoRR (2024)
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 (2024)
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)
Bhargav Samineni, S. M. Ferdous, Mahantesh Halappanavar, Bala Krishnamoorthy
Approximate Bipartite b-Matching using Multiplicative Auction. CoRR (2024)
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 (2023)
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)
Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti
Faster approximate subgraph counts with privacy. NeurIPS (2023)
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 (2023)
Rounak Meyur, Kostiantyn Lyman, Bala Krishnamoorthy, Mahantesh Halappanavar
Structural Validation of Synthetic Power Distribution Networks Using the Multiscale Flat Norm. ICCS (4) (2023)
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 (2023)
Ashutosh Dutta, Samrat Chatterjee, Arnab Bhattacharya, Mahantesh Halappanavar
Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties. CoRR (2023)
S. M. Ferdous, Bhargav Samineni, Alex Pothen, Mahantesh Halappanavar, Bala Krishnamoorthy
Streaming Algorithms for Weighted k-Disjoint Matchings. CoRR (2023)
Luis de la Torre, Mahantesh Halappanavar
Scaling Optimal Allocation of Cloud Resources Using Lagrange Relaxation. JSSPP (2023)
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)
Wenceslao Shaw-Cortez, Ján Drgona, Draguna L. Vrabie, Mahantesh Halappanavar
Robust Differentiable Predictive Control with Safety Guarantees: A Predictive Safety Filter Approach. CoRR (2023)
Lizhi Xiang, Arif M. Khan, S. M. Ferdous, Sr Aravind, Mahantesh Halappanavar
cuAlign: Scalable Network Alignment on GPU Accelerators. SC Workshops (2023)
Laya Das, Sai Munikoti, Mahantesh Halappanavar
There is more to graphs than meets the eye: Learning universal features with self-supervision. CoRR (2023)
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)
N. S. Karthik Somayaji, Yu Wang, Malachi Schram, Ján Drgona, Mahantesh Halappanavar, Frank Liu, Peng Li
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. CoRR (2023)
Ján Drgona, Sayak Mukherjee, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
Learning Stochastic Parametric Differentiable Predictive Control Policies. CoRR (2022)
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)
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)
Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
Neural Lyapunov Differentiable Predictive Control. CDC (2022)
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. Big Data (2022)
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)
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 (2022)
Wenceslao Shaw-Cortez, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. CoRR (2022)
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 (2022)
Sayan Ghosh, Nathan R. Tallent, Mahantesh Halappanavar
Characterizing Performance of Graph Neighborhood Communication Patterns. IEEE Trans. Parallel Distributed Syst. 33 (4) (2022)
Sai Munikoti, Balasubramaniam Natarajan, Mahantesh Halappanavar
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization. CoRR (2022)
Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
Neural Lyapunov Differentiable Predictive Control. CoRR (2022)
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)
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 (2022)
Nitin Gawande, Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman
Towards scaling community detection on distributed-memory heterogeneous systems. Parallel Comput. 111 (2022)
Xinyu Chen, Marco Minutoli, Jiannan Tian, Mahantesh Halappanavar, Ananth Kalyanaraman, Dingwen Tao
HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures. CoRR (2022)
Reet Barik, Marco Minutoli, Mahantesh Halappanavar, Ananth Kalyanaraman
IMpart: A Partitioning-based Parallel Approach to Accelerate Influence Maximization. HIPC (2022)
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)
Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar
On the Stochastic Stability of Deep Markov Models. CoRR (2021)
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)
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) (2021)
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)
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)
Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar
On the Stochastic Stability of Deep Markov Models. NeurIPS (2021)
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 (2021)
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 (2021)
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)
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 (2021)
S. M. Ferdous, Alex Pothen, Arif Khan, Ajay Panyala, Mahantesh Halappanavar
-Matching. ACDA (2021)
S. M. Ferdous, Alex Pothen, Arif Khan, Ajay Panyala, Mahantesh Halappanavar
A Parallel Approximation Algorithm for Maximizing Submodular b-Matching. CoRR (2021)
Mahantesh Halappanavar, Marco Minutoli, Sayan Ghosh
Graph analytics in the exascale era. CF (2021)
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)
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) (2020)
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) (2020)
Scott McMillan, Manoj Kumar, Danai Koutra, Mahantesh Halappanavar, Tim Mattson, Antonino Tumeo
Message from the workshop chairs. IPDPS Workshops (2020)
Marco Minutoli, Maurizio Drocco, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman
cuRipples: influence maximization on multi-GPU systems. ICS (2020)
Sayan Ghosh, Mahantesh Halappanavar
TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure. HPEC (2020)
Reet Barik, Marco Minutoli, Mahantesh Halappanavar, Nathan R. Tallent, Ananth Kalyanaraman
Vertex Reordering for Real-World Graphs and Applications: An Empirical Evaluation. IISWC (2020)
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)
Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman
Scaling and Quality of Modularity Optimization Methods for Graph Clustering. HPEC (2019)
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)
Sinan G. Aksoy, Emilie Purvine, Eduardo Cotilla Sanchez, Mahantesh Halappanavar
A generative graph model for electrical infrastructure networks. J. Complex Networks 7 (1) (2019)
Marco Minutoli, Mahantesh Halappanavar, Ananth Kalyanaraman, Arun V. Sathanur, Ryan Mcclure, Jason E. McDermott
Fast and Scalable Implementations of Influence Maximization Algorithms. CLUSTER (2019)
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)
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) (2019)
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)
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)
Ananth Kalyanaraman, Mahantesh Halappanavar
Guest Editorial: Advances in Parallel Graph Processing: Algorithms, Architectures, and Application Frameworks. IEEE Trans. Multi Scale Comput. Syst. 4 (3) (2018)
Antonino Tumeo, Mahantesh Halappanavar, John Feo, Assefaw Hadish Gebremedhin, Abhinav Vishnu
Introduction to GraML 2018. IPDPS Workshops (2018)
Arif Khan, Krzysztof Choromanski, Alex Pothen, S. M. Ferdous, Mahantesh Halappanavar, Antonino Tumeo
Adaptive anonymization of data using b-edge cover. SC (2018)
Florin Dobrian, Mahantesh Halappanavar, Alex Pothen, Ahmed Al-Herz
A 2/3-Approximation Algorithm for Vertex-weighted Matching in Bipartite Graphs. CoRR (2018)
Ryan D. Friese, Nathan R. Tallent, Malachi Schram, Mahantesh Halappanavar, Kevin J. Barker
Optimizing Distributed Data-Intensive Workflows. CLUSTER (2018)
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)
Craig Bakker, Mahantesh Halappanavar, Arun V. Sathanur
Dynamic graphs, community detection, and Riemannian geometry. Appl. Netw. Sci. 3 (1) (2018)
Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Assefaw H. Gebremedhin
MiniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems. PMBS@SC (2018)
Sayan Ghosh, Mahantesh Halappanavar, Antonino Tumeo, Ananth Kalyanaraman, Assefaw H. Gebremedhin
Scalable Distributed Memory Community Detection Using Vite. HPEC (2018)
Mahantesh Halappanavar, Hao Lu, Ananth Kalyanaraman, Antonino Tumeo
Scalable static and dynamic community detection using Grappolo. HPEC (2017)
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)
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 (2017)
Antonino Tumeo, Mahantesh Halappanavar, John Feo
Introduction to GraML Workshop. IPDPS Workshops (2017)
Sinan G. Aksoy, Emilie Purvine, Eduardo Cotilla Sanchez, Mahantesh Halappanavar
A generative graph model for electrical infrastructure networks. CoRR (2017)
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 (2017)
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) (2017)
Yu Hong Yeung, Alex Pothen, Mahantesh Halappanavar, Zhenyu Huang
AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids. CoRR (2017)
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) (2017)
Sudip Saha, Anil Vullikanti, Mahantesh Halappanavar
FlipNet: Modeling Covert and Persistent Attacks on Networked Resources. ICDCS (2017)
Ajay Panyala, Omer Subasi, Mahantesh Halappanavar, Ananth Kalyanaraman, Daniel G. Chavarría-Miranda, Sriram Krishnamoorthy
Approximate Computing Techniques for Iterative Graph Algorithms. HiPC (2017)
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)
Md. Naim, Fredrik Manne, Mahantesh Halappanavar, Antonino Tumeo
Community Detection on the GPU. IPDPS (2017)
Arun V. Sathanur, Mahantesh Halappanavar
Influence Maximization on Complex Networks with Intrinsic Nodal Activation. SocInfo (2) (2016)
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)
Fredrik Manne, Md. Naim, Håkon Lerring, Mahantesh Halappanavar
On Stable Marriages and Greedy Matchings. CSC (2016)
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)
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)
Arif M. Khan, Alex Pothen, Md. Mostofa Ali Patwary, Mahantesh Halappanavar, Nadathur Rajagopalan Satish, Narayanan Sundaram, Pradeep Dubey
-Matching algorithms on distributed memory multiprocessors by approximation. SC (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mahantesh Halappanavar