A new area is emerging at the intersection of artificial intelligence, machine learning, and systems design. This has been accelerated by the explosive growth of diverse applications of ML in production, the continued growth in data volume, and the complexity of large-scale learning systems. The goal of this workshop is to bring together experts working at the crossroads of machine learning, system design and software engineering to explore the challenges faced when building large-scale ML systems. In particular, we aim to elicit new connections among these diverse fields, identifying theory, tools and design principles tailored to practical machine learning workflows. We also want to think about best practices for research in this area and how to evaluate it. The workshop will cover state of the art ML and AI platforms and algorithm toolkits (e.g. TensorFlow, PyTorch1.0, MXNet etc.), as well as dive into machine learning-focused developments in distributed learning platforms, programming languages, data structures, hardware accelerators, benchmarking systems and other topics.
This workshop will follow the successful model we have previously run at ICML, NeurIPS and SOSP.
Our plan is to run this workshop annually co-located with one ML venue and one Systems venue, to help build a strong community which we think will complement newer conferences like SysML targeting research at the intersection of systems and machine learning. We believe this dual approach will help to create a low barrier to participation for both communities.
This workshop is part two of a two-part series with one day focusing on ML for Systems and the other on Systems for ML. Although the two workshops are being led by different organizers, we are coordinating our call for papers to ensure that the workshops complement each other and that submitted papers are routed to the appropriate venue.
Aparna Lakshmiratan (Facebook)
Siddhartha Sen (Microsoft Research)
Joseph Gonzalez (UC Berkeley)
Dan Crankshaw (UC Berkeley)
Sarah Bird (Microsoft)
More from the Same Authors
2019 Poster: ANODEV2: A Coupled Neural ODE Framework »
Tianjun Zhang · Zhewei Yao · Amir Gholami · Joseph Gonzalez · Kurt Keutzer · Michael W Mahoney · George Biros
2018 Workshop: MLSys: Workshop on Systems for ML and Open Source Software »
Aparna Lakshmiratan · Sarah Bird · Siddhartha Sen · Joseph Gonzalez · Daniel Crankshaw
2018 Workshop: Workshop on Ethical, Social and Governance Issues in AI »
Chloe Bakalar · Sarah Bird · Tiberio Caetano · Edward W Felten · Dario Garcia · Isabel Kloumann · Finnian Lattimore · Sendhil Mullainathan · D. Sculley
2017 Workshop: ML Systems Workshop @ NIPS 2017 »
Aparna Lakshmiratan · Sarah Bird · Siddhartha Sen · Christopher Ré · Li Erran Li · Joseph Gonzalez · Daniel Crankshaw
2016 Workshop: Machine Learning Systems »
Aparna Lakshmiratan · Li Erran Li · Siddhartha Sen · Sarah Bird · Hussein Mehanna