Jul 16, 2023 · Abstract:In distributed training, deep neural networks (DNNs) are launched over multiple workers concurrently and aggregate their local ...
Missing: (Poster | Show results with:(Poster
In SelSync, we combine parallel and statistical efficiencyof distributed data-parallel training and develop a practical,low-overhead method that dynamically ...
Posters. Conference Paper. Accelerating Distributed ML Training via Selective Synchronization (Poster Abstract). October 2023. DOI:10.1109/CLUSTERWorkshops61457 ...
Accelerating Distributed ML Training via Selective. Synchronization (Poster Abstract) ... “More Effective Distributed ML via a Stale Synchronous Parallel.
Show abstract. Taming Resource Heterogeneity In Distributed ML Training With Dynamic Batching. Conference Paper. Full-text available. Jul 2020. Sahil ...
Missing: (Poster | Show results with:(Poster
This paper presents SelSync, a practical, low-overhead method for DNN training that dynamically chooses to incur or avoid communication at each step either ...
Missing: Abstract). | Show results with:Abstract).
Aug 5, 2024 · Accelerating Distributed ML Training via Selective Synchronization (Poster Abstract). CLUSTER Workshops 2023: 56-57. [i7]. view. electronic ...
Sep 27, 2022 · Abstract. Geo-distributed machine learning (Geo-DML) adopts a hierarchical training architecture that includes local model synchronization ...
Missing: Selective (Poster
Aug 4, 2024 · In this paper, we identify unique opportunities to accelerate training and propose StellaTrain, a holistic framework that achieves near-optimal training speeds ...
Feb 4, 2022 · We introduce the distributed asynchronous and selective optimization (DASO) method, which leverages multi-GPU compute node architectures to accelerate network ...
Missing: ML (Poster