ML for Computer Architecture and Systems
Call for Papers
Learned models for computer architecture and systems optimization
Machine learning techniques for compiler and code optimization
Distributed systems for machine learning workloads
Machine learning for hardware/software co-design
Automated machine learning in EDA tools
Architecture and accelerator design for machine learning models
Evaluation of machine learning systems and architectures
We welcome submissions of up to 4 pages (not including references). This is not a strict limit, but authors are encouraged to adhere to it if possible.
All submissions must be in PDF format and should follow the ISCA'21 Latex Template.
Please follow the guidelines provided at ISCA 2021 Paper Submission Guidelines.
Please submit your paper no later than May 16th, 2021 - Midnight Anywhere on Earth.
Reviewing will be double blind: please do not include any author names on any submitted documents except in the space provided on the submission form.
Milad Hashemi (Google Research)
Akanksha Jain (University of Texas at Austin)
Mangpo Phothilimthana (Google Research)
Neeraja J. Yadwadkar (Stanford)
Amir Yazdanbakhsh (Google Research)
Mojan Javaheripi (UCSD)
Ryan Marcus (MIT)
Daniel Berger (Microsoft)
Cliff Young (Google)
Sangeetha Jyothi (UCI)
Avani Wildani (Emory)
Chris Cummins (Facebook AI Research)
Dan Zheng (Google)
Yanqi Zhou (Google)
Berkin Akin (Google)
Soroush Ghodrati (UCSD)
Liang Luo (Facebook)
Shreya Rajpal (University of Illinois, Urbana-Champaign)
Contact us at firstname.lastname@example.org