Communication-Avoiding Linear Algebraic Kernel K-Means on GPUs - Julian Bellavita; Matthew Rubino; Nakul Iyer; Andrew Chang; Aditya Devarakonda; Flavio Vella; Giulia Guidi (CoRR, 2026)

Scalable Dual Coordinate Descent for Kernel Methods - Zishan Shao; Aditya Devarakonda (Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2025, Hsinchu, Taiwan, February 19-21, 2025, 2025)

Parallel Rank-Adaptive Higher Order Orthogonal Iteration - João Pinheiro; Aditya Devarakonda; Grey Ballard (Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2025, St. Louis, MO, USA, November 16-21, 2025, 2025)

Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization - Aditya Devarakonda; Ramakrishnan Kannan (CoRR, 2025)

DistShap: Scalable GNN Explanations with Distributed Shapley Values - Selahattin Akkas; Aditya Devarakonda; Ariful Azad (CoRR, 2025)

Enhanced Cyclic Coordinate Descent Methods for Elastic Net Penalized Linear Models - Yixiao Wang; Zishan Shao; Ting Jiang; Aditya Devarakonda (CoRR, 2025)

Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths - Aditya Devarakonda; Grey Ballard (Proceedings of the 2024 SIAM Conference on Parallel Processing for Scientific Computing, PP 2024, Baltimore, MD, USA, March 5-8, 2024, 2024)

Scalable Dual Coordinate Descent for Kernel Methods - Zishan Shao; Aditya Devarakonda (CoRR, 2024)

Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths - Aditya Devarakonda; Grey Ballard (CoRR, 2023)

Avoiding Communication in Logistic Regression - Aditya Devarakonda; James Demmel (27th IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2020, Pune, India, December 16-19, 2020, 2020)

Avoiding Communication in Logistic Regression - Aditya Devarakonda; James Demmel (CoRR, 2020)

Avoiding Communication in Primal and Dual Block Coordinate Descent Methods - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (SIAM J. Sci. Comput., 2019)

Avoiding Communication in First Order Methods for Optimization - Aditya Devarakonda (University of California, Berkeley, USA, 2018)

Reducing Communication in Proximal Newton Methods for Sparse Least Squares Problems - Saeed Soori; Aditya Devarakonda; Zachary Blanco; James Demmel; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (Proceedings of the 47th International Conference on Parallel Processing, ICPP 2018, Eugene, OR, USA, August 13-16, 2018, 2018)

Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (2018 IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018, Vancouver, BC, Canada, May 21-25, 2018, 2018)

Avoiding Communication in Proximal Methods for Convex Optimization Problems - Saeed Soori; Aditya Devarakonda; James Demmel; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (CoRR, 2017)

AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks - Aditya Devarakonda; Maxim Naumov; Michael Garland (CoRR, 2017)

Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (CoRR, 2017)

Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies - Alex Gittens; Aditya Devarakonda; Evan Racah; Michael F. Ringenburg; Lisa Gerhardt; Jey Kottalam; Jialin Liu; Kristyn J. Maschhoff; Shane Canon; Jatin Chhugani; Pramod Sharma; Jiyan Yang; et al. (2016 IEEE International Conference on Big Data (IEEE BigData 2016), Washington DC, USA, December 5-8, 2016, 2016)

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies - Alex Gittens; Aditya Devarakonda; Evan Racah; Michael F. Ringenburg; Lisa Gerhardt; Jey Kottalam; Jialin Liu; Kristyn J. Maschhoff; Shane Canon; Jatin Chhugani; Pramod Sharma; Jiyan Yang; et al. (CoRR, 2016)

Avoiding communication in primal and dual block coordinate descent methods - Aditya Devarakonda; Kimon Fountoulakis; James Demmel; Michael W. Mahoney (CoRR, 2016)

Architecting an autograder for parallel code - Razvan Carbunescu; Aditya Devarakonda; James Demmel; Steven I. Gordon; Jay Alameda; Susan Mehringer (Annual Conference of the Extreme Science and Engineering Discovery Environment, XSEDE '14, Atlanta, GA, USA - July 13 - 18, 2014, 2014)

Cloud Paradigms and Practices for Computational and Data-Enabled Science and Engineering - Manish Parashar; Moustafa AbdelBaky; Ivan Rodero; Aditya Devarakonda (Comput. Sci. Eng., 2013)

Cloud federation in a layered service model - David Villegas; Norman Bobroff; Ivan Rodero; Javier Delgado; Yanbin Liu; Aditya Devarakonda; Liana Fong; Seyed Masoud Sadjadi; Manish Parashar (J. Comput. Syst. Sci., 2012)