Workshop Overview
Machine Learning for Systems is an interdisciplinary workshop that brings together researchers in computer systems and machine learning, specifically focusing on the novel application of machine learning techniques towards computer systems problems.
Call for Papers
We invite submission of up to 4-page extended abstracts in the broad area of using machine learning in the design and management of computer systems . We are especially interested in submissions that move beyond using machine learning to replace numerical heuristics.
This year, we additionally look for
- Using LLMs for systems challenges, such as program synthesis for hardware and other specialized domains.
- Applying ML to systems issues that emerge from large-scale training and serving, such as compiler partitioning schemes for training LLMs across thousands of GPU or TPU devices.
- Applying ML for compute sustainability, including power/energy/carbon optimization. Examples include energy-aware job scheduling, dynamic power management based on workload and carbon predictions, and ML-driven carbon footprint assessment for cloud datacenters.
Accepted papers will be optionally linked on the workshop website, but there will be no formal proceedings. Authors may therefore publish their work in other journals or conferences. The workshop will include invited talks from industry and academia, as well as oral and poster presentations by workshop participants.
You can find accepted papers to the previous iteration of ML for Systems from NeurIPS 2023, NeurIPS 2022, 2021, 2020, 2019, 2018, and ISCA 2019.
Accepted papers will be made available on the workshop website, but there will be no formal proceedings. Authors may therefore publish their work in other journals or conferences. The workshop will include invited talks from industry and academia as well as oral and poster presentations by workshop participants.
Camera-Ready Instructions
For accepted papers, please update the camera-ready manuscript on OpenReview by Oct 28th AoE.
Please see instructions below:
- Please address the AC comments (if any) and use the reviews to improve the paper.
- The camera-ready template is the same as the one used for submission, which is same as NeurIPS papers but using `Final` package. We have made some minor changes to the format. Please update with the template (.zip) attached.
- There is a hard page limit of 4 pages (excluding references and Appendix).
- Appendix and references do not have a limit.