An Overview of the Data-Loader Landscape: Numerical Results Cont.

Written by serialization | Published 2024/06/04
Tech Story Tags: data-loaders | machine-learning | training-performance | deep-learning | data-loading | remote-storage | gpu-training | dataloading-libraries

TLDRIn this paper, researchers highlight dataloaders as key to improving ML training, comparing libraries for functionality, usability, and performance.via the TL;DR App

Authors:

(1) Iason Ofeidis, Department of Electrical Engineering, and Yale Institute for Network Science, Yale University, New Haven {Equal contribution};

(2) Diego Kiedanski, Department of Electrical Engineering, and Yale Institute for Network Science, Yale University, New Haven {Equal contribution};

(3) Leandros TassiulasLevon Ghukasyan, Activeloop, Mountain View, CA, USA, Department of Electrical Engineering, and Yale Institute for Network Science, Yale University, New Haven.

Table of Links

A. NUMERICAL RESULTS CONT.

In this appendix, we include a collection of plots for which we did not have space in the core pages of the article.

This paper is available on arxiv under CC 4.0 license.


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Published by HackerNoon on 2024/06/04