Aditya Devarakonda

According to our database, Aditya Devarakonda authored at least 14 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Proceedings of the 2024 SIAM Conference on Parallel Processing for Scientific Computing, 2024

2020

Avoiding Communication in Logistic Regression.

Aditya Devarakonda, James Demmel

Proceedings of the 27th IEEE International Conference on High Performance Computing, 2020

2019

Avoiding Communication in Primal and Dual Block Coordinate Descent Methods.

Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney

SIAM J. Sci. Comput., 2019

2018

Avoiding Communication in First Order Methods for Optimization.

Aditya Devarakonda

PhD thesis, 2018

Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization.

Aditya Devarakonda, Kimon Fountoulakis, James Demmel, Michael W. Mahoney

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 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, 2018

2017

AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks.

Aditya Devarakonda, Maxim Naumov, Michael Garland

CoRR, 2017

Avoiding Communication in Proximal Methods for Convex Optimization Problems.

Saeed Soori, Aditya Devarakonda, James Demmel, Mert Gürbüzbalaban, Maryam Mehri Dehnavi

CoRR, 2017

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, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat

CoRR, 2016

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, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2014

Architecting an autograder for parallel code.

Razvan Carbunescu, Aditya Devarakonda, James Demmel, Steven I. Gordon, Jay Alameda, Susan Mehringer

Proceedings of the Annual Conference of the Extreme Science and Engineering Discovery Environment, 2014

2013

Cloud Paradigms and Practices for Computational and Data-Enabled Science and Engineering.

Manish Parashar, Moustafa AbdelBaky, Ivan Rodero, Aditya Devarakonda

Comput. Sci. Eng., 2013

2012

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