@inproceedings{6b983b3a31d94adfac39da8eb4854ff7,
title = "A comparison of ARM against x86 for distributed machine learning workloads",
abstract = "The rise of Machine Learning (ML) in the last decade has created an unprecedented surge in demand for new and more powerful hardware. Various hardware approaches exist to take on these large demands motivating the need for hardware performance benchmarks to compare these diverse hardware systems. In this paper, we present a comprehensive analysis and comparison of available benchmark suites in the field of ML and related fields. The analysis of these benchmarks is used to discuss the potential of ARM processors within the context of ML deployments. Our paper concludes with a brief hardware performance comparison of modern, server-grade ARM and x86 processors using a benchmark suite selected from our survey.",
keywords = "ARM, Benchmark, Distributed, Machine learning, x86",
author = "Sebastian Kmiec and Jonathon Wong and Jacobsen, {Hans Arno} and Ren, {Da Qi}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.; 9th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2017, held in conjunction with the 43rd International Conference on Very Large Data Bases, VLDB 2017 ; Conference date: 28-08-2017 Through 01-09-2017",
year = "2018",
doi = "10.1007/978-3-319-72401-0_12",
language = "English",
isbn = "9783319724003",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "164--184",
editor = "Meikel Poess and Raghunath Nambiar",
booktitle = "Performance Evaluation and Benchmarking for the Analytics Era - 9th TPC Technology Conference, TPCTC 2017, Revised Selected Papers",
}