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.
How to Join
Use this link to request to join the group/mailing list, and receive the meeting invite:
Mobile Google Group.
Requests are manually reviewed, so please be patient.
Working Group Resources
Shared documents and meeting minutes:
- Associate a Google account with your e-mail address.
- Ask to join our Public Google Group.
- Ask to join our Members Google Group.
- Once approved, go to the Mobile folder in the Members Google Drive.
Working Group Chair Emails
William Chou (wchou@qti.qualcomm.com)
Manasa Kankanala (manasa.kankanala@intel.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.
Manasa Kankanala is a AI Engineer at Intel. She has over 6 years of experience in performance benchmarking. Manasa has a Bachelors Degree in Engineering and a Masters Degree in Computer Science.