MLI: An API for Distributed Machine Learning

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.

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• GraphLab: A New Framework For Parallel Machine Learning
• Scaling Datalog for Machine Learning on Big Data
• The MADlib Analytics Library or MAD Skills, the SQL

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