Inference Working Group
Mobile Working Group
- Overview
- Training Working Group
- Inference Working Group
- Datasets Working Group
- Best Practices Working Group
- Research Working Group
Mission
Create a set of fair and representative inference benchmarks for mobile consumer devices such as smartphones, tablets, and notebooks that is representative of the end user experience.
Purpose
The MLPerf™ Mobile working group aims to collaboratively develop a performance-accuracy benchmark suite for consumer mobile devices with different AI chips and software stacks. The MLPerf Mobile working group draws from the expertise of mobile SoC vendors, ML framework providers, and model producers, and extends the MLPerf inference group’s efforts to a mobile context. We welcome new members that hope to raise the bar of ML performance for mobile devices.
Deliverables
- Mobile benchmark rules and definitions
- Mobile benchmark reference software
- Mobile benchmark submission rules
- Mobile benchmark roadmap
- Mobile benchmark app for Android and iOS (future version)
- Publish mobile benchmark results every ~6 months
Meeting Schedule
Weekly on Wednesday from 3:00-4:00PM Pacific.
Mailing List
Working Group Resources
Working Group Chair Emails
William Chou (wchou@qti.qualcomm.com)
Ramesh Chukka (ramesh.n.chukka@intel.com)
Jungwook Hong (jwookie.hong@samsung.com)
Working Group Chair Bios
William Chou is a Product Manager at Qualcomm and he received his undergraduate and Master’s degree from the University of Toronto.
Ramesh Chukka is a Deep Learning Manager at Intel with focus on performance analysis and benchmarking. He has 14+ years of experience leading benchmark development and working with industry benchmark consortiums. Ramesh received M.Tech from IIT Madras and B.E from Andhra University, India.
Jungwook (Wookie) Hong is an SoC product planner at Samsung Electronics’s S.LSI business and he received his undergraduate degree at the University of Virginia.