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MLI: An API for Distributed Machine Learning

Authors :
Sparks, Evan R.
Talwalkar, Ameet
Smith, Virginia
Kottalam, Jey
Pan, Xinghao
Gonzalez, Joseph
Franklin, Michael J.
Jordan, Michael I.
Kraska, Tim
Publication Year :
2013

Abstract

MLI is an Application Programming Interface designed to address the challenges of building Machine Learn- ing algorithms in a distributed setting based on data-centric computing. Its primary goal is to simplify the development of high-performance, scalable, distributed algorithms. Our initial results show that, relative to existing systems, this interface can be used to build distributed implementations of a wide variety of common Machine Learning algorithms with minimal complexity and highly competitive performance and scalability.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1310.5426
Document Type :
Working Paper