Publications

Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters

Foteini Strati*, Zhendong Zhang, George Manos, Ixeia Sánchez Périz, Qinghao Hu, Tiancheng Chen, Berk Buzcu, Song Han, Pamela Delgado, Ana Klimovic, In ACM SIGOPS 31st Symposium on Operating Systems Principles (SOSP ’25), October 13–16, 2025, Seoul, Republic of Korea.

Measuring GPU utilization one level deeper

Paul Elvinger, Foteini Strati, Natalie Enright Jerger, Ana Klimovic, Under submission

PCcheck: Persistent Concurrent Checkpointing for ML

Foteini Strati*, Michal Friedman*, Ana Klimovic, In Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2025)

ML Training with Cloud GPU Shortages: Is Cross-Region the Answer?

Foteini Strati, Paul Elvinger, Tolga Kerimoglu, Ana Klimovic (ETH Zurich), In Proceedings of the 4th Workshop on Machine Learning and Systems (EuroMLSys 2024)

DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving

Foteini Strati, Sara Mcallister, Amar Phanishayee, Jakub Tarnawski, Ana Klimovic, In Proceedings of the 41st International Conference on Machine Learning (ICML 2024)

Orion: Interference-aware, Fine-grained GPU Sharing for ML Applications

Foteini Strati, Xianzhe Ma, Ana Klimovic, In Proceedings of the Nineteenth European Conference on Computer Systems (EuroSys 2024)

Towards A Platform and Benchmark Suite for Model Training on Dynamic Datasets

Maximilian Böther, Foteini Strati, Viktor Gsteiger, and Ana Klimovic. 2023. Towards A Platform and Benchmark Suite for Model Training on Dynamic Datasets. In Proceedings of the 3rd Workshop on Machine Learning and Systems (EuroMLSys 2023).8–17.

Exploring learning rate scaling rules for distributed ML training on transient resources

Joel André*, Foteini Strati*, and Ana Klimovic. 2022. Exploring learning rate scaling rules for distributed ML training on transient resources. In Proceedings of the 3rd International Workshop on Distributed Machine Learning (DistributedML 2022). 1–8

An adaptive concurrent priority queue for numa architectures

Foteini Strati*, Christina Giannoula*, Dimitrios Siakavaras, Georgios Goumas, and Nectarios Koziris. 2019. An adaptive concurrent priority queue for NUMA architectures. In Proceedings of the 16th ACM International Conference on Computing Frontiers (CF 2019), 135–144.