Principal Component Networks: Parameter Reduction Early in Training. - Roger Waleffe; Theodoros Rekatsinas (CoRR, 2020)

Marius: Learning Massive Graph Embeddings on a Single Machine. - Jason Mohoney; Roger Waleffe; Henry Xu; Theodoros Rekatsinas; Shivaram Venkataraman (OSDI, 2021)

Learning Massive Graph Embeddings on a Single Machine. - Jason Mohoney; Roger Waleffe; Yiheng Xu; Theodoros Rekatsinas; Shivaram Venkataraman (CoRR, 2021)

Demonstration of Marius: Graph Embeddings with a Single Machine. - Anders Carlsson; Anze Xie; Jason Mohoney; Roger Waleffe; Shanan Peters; Theodoros Rekatsinas; Shivaram Venkataraman (Proc. VLDB Endow., 2021)

Marius++: Large-Scale Training of Graph Neural Networks on a Single Machine. - Roger Waleffe; Jason Mohoney; Theodoros Rekatsinas; Shivaram Venkataraman (CoRR, 2022)

MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks. - Roger Waleffe; Jason Mohoney; Theodoros Rekatsinas; Shivaram Venkataraman (EuroSys, 2023)

Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. - Patrik Okanovic; Roger Waleffe; Vasilis Mageirakos; Konstantinos E. Nikolakakis; Amin Karbasi; Dionysios S. Kalogerias; Nezihe Merve Gürel; Theodoros Rekatsinas (ICLR, 2024)

An Empirical Study of Mamba-based Language Models. - Roger Waleffe; Wonmin Byeon; Duncan Riach; Brandon Norick; Vijay Korthikanti; Tri Dao; Albert Gu; Ali Hatamizadeh; Sudhakar Singh 003; Deepak Narayanan; Garvit Kulshreshtha; Vartika Singh; et al. (CoRR, 2024)

GraphSnapShot: Graph Machine Learning Acceleration with Fast Storage and Retrieval. - Dong Liu; Roger Waleffe; Meng Jiang; Shivaram Venkataraman (CoRR, 2024)

Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models. - Wenqi Jiang 001; Marco Zeller; Roger Waleffe; Torsten Hoefler; Gustavo Alonso (Proc. VLDB Endow., 2024)

MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. - Yongjun He 004; Roger Waleffe; Zhichao Han 001; Johnu George; Binhang Yuan; Zitao Zhang; Yinan Shan; Yang Zhao; Debojyoti Dutta; Theodoros Rekatsinas; Ce Zhang 001 (ICDE, 2025)

Armada: Memory-Efficient Distributed Training of Large-Scale Graph Neural Networks. - Roger Waleffe; Devesh Sarda; Jason Mohoney; Emmanouil-Vasileios Vlatakis-Gkaragkounis; Theodoros Rekatsinas; Shivaram Venkataraman (CoRR, 2025)

Llama-Nemotron: Efficient Reasoning Models. - Akhiad Bercovich; Itay Levy; Izik Golan; Mohammad Dabbah; Ran El-Yaniv; Omri Puny; Ido Galil; Zach Moshe; Tomer Ronen; Najeeb Nabwani; Ido Shahaf; Oren Tropp; et al. (CoRR, 2025)