3 papers
cs.DC2025
Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters
Foteini Strati, Zhendong Zhang, George Manos +7
The high GPU demand of ML training makes it hard to allocate large homogeneous clusters of high-end GPUs in a single availability zone. Leveraging heterogeneous GPUs available with…
cs.DC2025
Understanding GPU Resource Interference One Level Deeper
Paul Elvinger, Foteini Strati, Natalie Enright Jerger +1
GPUs are vastly underutilized, even when running resource-intensive AI applications, as GPU kernels within each job have diverse resource profiles that may saturate some parts of a…
cs.DC2024
SmartPQ: An Adaptive Concurrent Priority Queue for NUMA Architectures
Christina Giannoula, Foteini Strati, Dimitrios Siakavaras +2
Concurrent priority queues are widely used in important workloads, such as graph applications and discrete event simulations. However, designing scalable concurrent priority queues…