Federated Learning

When RDMA Goes Long-Haul: Characterization, Modeling, and Verbs-Level Emulation with Implications for Federated Learning

Characterization, modeling, and verbs-level emulation of long-haul RDMA with implications for federated learning.

Jan 1, 2026

FedMECA: Scalable Federated Learning via Memory-Efficient and Concurrent Aggregation

Scalable federated learning via memory-efficient and concurrent aggregation.

Jan 1, 2026

Scalable, Resilient Federated Learning

SRFL targets scalable and resilient federated learning systems across heterogeneous compute and network environments. The project includes: FedDES, a discrete-event based performance simulation framework for federated learning systems. FedMECA, a memory-efficient and concurrent aggregation approach for scalable federated learning. Long-haul RDMA studies for geo-distributed federated learning, including simulation, modeling, and real-world testbed validation.

Jan 1, 2025

Long-Haul RDMA

This project investigates long-haul RDMA for geo-distributed machine learning systems. The project includes: Characterization, modeling, and verbs-level emulation of long-haul RDMA behavior. Evaluation of whether long-haul RDMA can improve geo-distributed federated learning, including simulation and validation on a real-world testbed.

Jan 1, 2025

FedDES: Discrete Event Based Performance Simulation for Federated Learning Systems

Discrete-event based performance simulation for federated learning systems across heterogeneous compute/network settings.

Jan 1, 2025

Can Long-Haul RDMA Benefit Federated Learning?

Communication-centric study of long-haul RDMA for geo-distributed federated learning.

Jan 1, 2025