1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
Sublinear Metric Steiner Tree via Improved Bounds for Set Cover
Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski +1
We study the metric Steiner tree problem in the sublinear query model. In this problem, for a set of points in a metric space given to us by means of query access to an $n\…
Integrated Hardware Architecture and Device Placement Search
Irene Wang, Jakub Tarnawski, Amar Phanishayee +1
Distributed execution of deep learning training involves a dynamic interplay between hardware accelerator architecture and device placement strategy. This is the first work to expl…
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi +2
Many methods in differentially private model training rely on computing the similarity between a query point (such as public or synthetic data) and private data. We abstract out th…
DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving
Foteini Strati, Sara Mcallister, Amar Phanishayee +2
Distributed LLM serving is costly and often underutilizes hardware accelerators due to three key challenges: bubbles in pipeline-parallel deployments caused by the bimodal latency…