3 papers
cs.DC2026
SENTINEL: Stagewise Integrity Verification for Pipeline Parallel Decentralized Training
Hadi Mohaghegh Dolatabadi, Thalaiyasingam Ajanthan, Sameera Ramasinghe +5
Decentralized training introduces critical security risks when executed across untrusted, geographically distributed nodes. While existing Byzantine-tolerant literature addresses d…
cs.LG2026
AsyncMesh: Fully Asynchronous Optimization for Data and Pipeline Parallelism
Thalaiyasingam Ajanthan, Sameera Ramasinghe, Gil Avraham +5
Data and pipeline parallelism are key strategies for scaling neural network training across distributed devices, but their high communication cost necessitates co-located computing…
cs.LG2025
Nesterov Method for Asynchronous Pipeline Parallel Optimization
Thalaiyasingam Ajanthan, Sameera Ramasinghe, Yan Zuo +2
Pipeline Parallelism (PP) enables large neural network training on small, interconnected devices by splitting the model into multiple stages. To maximize pipeline utilization, asyn…