2 papers
cs.DC2026
Eidola: Modeling Multi-GPU Network Communication Traffic in Distributed AI Workloads
Ranganath R. Selagamsetty, Matthew Poremba, Bradford M. Beckmann +2
As distributed AI workloads grow in scale, multi-GPU systems have become essential for training large models. Although techniques like kernel fusion and overlapping communication w…
cs.CR2025
CryptOracle: A Modular Framework to Characterize Fully Homomorphic Encryption
Cory Brynds, Parker McLeod, Lauren Caccamise +5
Privacy-preserving machine learning has become an important long-term pursuit in this era of artificial intelligence (AI). Fully Homomorphic Encryption (FHE) is a uniquely promisin…