WAX 2017 Program
Sunday, April 9, 2017
Chang Le Room
9:00–9:15am: Opening and introductions
Be ready to introduce yourself!
Lingjia Tang, University of Michigan: “Scalable Approximation Computing: a Cross-Layer Solution.”
10:00am–10:15am: Lightning talks
- Ming Liu, University of Washington: Approximating Data-plane Algorithms on the Programmable Switch
- Adrian Sampson, Cornell University: QuEST, the Quality-Efficient System Tournament
- Luis Ceze, University of Washington: Towards a Wet-Dry Computer
10:30–11:30am: Paper talks
Talks are 10 minutes each. There will be a 3-minute moment for questions immediately afterward; in the rest of the time, all the speakers will be available to answer more questions from attendees.
- Leveraging Approximation to Increase Resource-Efficiency in the Cloud. Neeraj Kulkarni, Feng Qi, Glyfina Fernando, and Christina Delimitrou (Cornell University). Slides.
- Motivating In-Network Aggregation for Distributed Deep Neural Network Training. Liang Luo and Luis Ceze (University of Washington).
- Leveraging Software Testing to Explore Input Dependence for Approximate Computing. Abdulrahman Mahmoud, Radha Venkatagiri, Khalique Ahmed, Sarita Adve, Darko Marinov, and Sasa Misailovic (University of Illinois at Urbana-Champaign).
- Rethinking the Camera Pipeline for Computer Vision. Mark Buckler (Cornell University), Suren Jayasuriya (CMU), and Adrian Sampson (Cornell University). Slides.
11:30–noon: Panel and discussion