Nikoli Dryden
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
16
Venues
10
Active years
2015–2026
Best venue rank
A*
Where they publish
Papers
16 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | HPDC | CoDL: A Framework for Studying Cross-Component Interference in Deep Learning Training Pipelines. | Druva Dhakshinamoorthy, Ray A. O. Sinurat, Nikoli Dryden, Arnab K. Paul, Hariharan Devarajan |
| 2026 | SSDBM | HORATIO: Bridging Management and Analysis of Traces at Scale. | Ray A. O. Sinurat, William Nixon, Haryadi S. Gunawi, Nikoli Dryden, Hariharan Devarajan |
| 2026 | SSDBM | WADO: A Distributed WORM Storage Service for Asynchronous Data Operations. | Karim Youssef, Hariharan Devarajan, Nikoli Dryden, Roger Pearce |
| 2025 | ICS | Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers. | Chen Zhuang, Lingqi Zhang, Du Wu, Peng Chen, Jiajun Huang, Xin Liu, Rio Yokota, Nikoli Dryden, Toshio Endo, Satoshi Matsuoka, Mohamed Wahib |
| 2025 | PPoPP | A General and Scalable GCN Training Framework on CPU Supercomputers. | Chen Zhuang, Peng Chen, Xin Liu, Rio Yokota, Nikoli Dryden, Lingqi Zhang, Toshio Endo, Satoshi Matsuoka, Mohamed Wahib |
| 2024 | WACV | Learning to Compose SuperWeights for Neural Parameter Allocation Search. | Piotr Teterwak, Soren Nelson, Nikoli Dryden, Dina Bashkirova, Kate Saenko, Bryan A. Plummer |
| 2022 | ICLR | Neural Parameter Allocation Search. | Bryan A. Plummer, Nikoli Dryden, Julius Frost, Torsten Hoefler, Kate Saenko |
| 2022 | ICS | A data-centric optimization framework for machine learning. | Oliver Rausch, Tal Ben-Nun, Nikoli Dryden, Andrei Ivanov, Shigang Li, Torsten Hoefler |
| 2022 | KDD | Motif Prediction with Graph Neural Networks. | Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler |
| 2021 | SC | Clairvoyant prefetching for distributed machine learning I/O. | Nikoli Dryden, Roman Bhringer, Tal Ben-Nun, Torsten Hoefler |
| 2019 | SC | Channel and filter parallelism for large-scale CNN training. | Nikoli Dryden, Naoya Maruyama, Tim Moon, Tom Benson, Marc Snir, Brian Van Essen |
| 2018 | CLUSTER | Neural Network Based Silent Error Detector. | Chen Wang, Nikoli Dryden, Franck Cappello, Marc Snir |
| 2018 | PLDI | Gluon: a communication-optimizing substrate for distributed heterogeneous graph analytics. | Roshan Dathathri, Gurbinder Gill, Loc Hoang, Hoang-Vu Dang, Alex Brooks, Nikoli Dryden, Marc Snir, Keshav Pingali |
| 2017 | SC | Towards Scalable Parallel Training of Deep Neural Networks. | Sam Ade Jacobs, Nikoli Dryden, Roger A. Pearce, Brian Van Essen |
| 2016 | SC | Communication Quantization for Data-Parallel Training of Deep Neural Networks. | Nikoli Dryden, Tim Moon, Sam Ade Jacobs, Brian Van Essen |
| 2015 | SC | PPL: an abstract runtime system for hybrid parallel programming. | Alex Brooks, Hoang-Vu Dang, Nikoli Dryden, Marc Snir |