Jul 2, 2022 · 1 INTRODUCTION. Geo-distributed machine learning (Geo-DML) systems, which pro- vide the ability of learning models from massive data across ...
Efficient Partial Reduce Across Clouds · Contents. APNet '22: Proceedings of the 6th Asia-Pacific Workshop on Networking. Efficient Partial Reduce Across Clouds.
Sep 13, 2024 · Current partial reduce solutions are mainly designed for intra-cluster DML, in which workers are networked with high-bandwidth LAN links. Yet no ...
Missing: Across | Show results with:Across
To address the above challenges, we propose CREW, a flexible and efficient partial reduce implementation that builds upon the design of “weighted sC atter, ...
Semantic Scholar extracted view of "Efficient Partial Reduce Across Clouds" by Renyi Wang et al.
A more cost-efficient option are hyperscale clouds offering spot instances, a cheap but ephemeral alternative to on-demand resources. As spot instance ...
Sep 13, 2024 · To fill the gap, in this paper, we propose <sc>CREW</sc>, a flexible and efficient implementation of <italic>partial reduce</italic> for cross- ...
Oct 22, 2024 · To fill the gap, in this paper, we propose CREW , a flexible and efficient implementation of partial reduce for cross-cloud DML. At the high ...
This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space ...
The experiments show that using low-frequency (daily or monthly) time-averaged model output of the cloud property fields underestimates the ERF, but 3-hourly ...