1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.DC2024★ 1 cited
Guardian: Safe GPU Sharing in Multi-Tenant Environments
Manos Pavlidakis, Giorgos Vasiliadis, Stelios Mavridis +3
Modern GPU applications, such as machine learning (ML), can only partially utilize GPUs, leading to GPU underutilization in cloud environments. Sharing GPUs across multiple applica…
eess.SY2023★ 1 cited
Arax: A Runtime Framework for Decoupling Applications from Heterogeneous Accelerators
Manos Pavlidakis, Stelios Mavridis, Antony Chazapis +2
Today, using multiple heterogeneous accelerators efficiently from applications and high-level frameworks, such as TensorFlow and Caffe, poses significant challenges in three respec…