October 2nd, 2020
In conjunction with PACT20, Atlanta, GA
As Machine Learning (ML) continues to permeate all areas of computing, software system designers and software stack developers are adopting ML solutions and designs to solve challenging problems presented in their areas; especially in areas like optimization and hardware design. ML is increasingly being used to solve a diverse set of problems such as the design of cost models, code optimization heuristics, efficient search space exploration, automatic optimization, and program synthesis. Designing accurate machine learning models, feature engineering, verification, and validation of obtained results and selecting and curating representative training data are all examples of challenging but important problems in this area that are actively being explored by a large community of researchers in industry and academia. This workshop provides a great venue for the international research community to share ideas and techniques to apply machine learning to system challenges with a focus on the software stack and hardware.
ScopeWe will solicit papers on topics including, but not limited to, the following areas:
We invite both full-length research papers and short research
papers.
The submitted paper should not exceed the page limit (8 pages for
full-length and 4 pages for short papers) and should follow the IEEE
conference proceedings templates.
The page limit applies to all content NOT including references, and there is no page limit for references.
The submission will be reviewed by at least three program committee
members and should not have published in or under review for another
venue.
Accepted papers will be published in our online proceedings.
Submit your paper using this link.