March 9, 2018

Announcing the winners of the Facebook Hardware & Software Systems research awards

By: Facebook Research

Continued research into hardware and systems is essential to Facebook as we develop algorithms to maximize impact and every day experiences. By sponsoring research, we extend our knowledge and share findings. We are especially interested in collaborating and sponsoring research at the intersection of computer systems and machine learning and are pleased to announce the following winners of the Hardware and Software Systems Research Award. Below are the winners and their topic areas.

DAWNBench: An End-to-End Deep Learning Performance Benchmark
Matei Zaharia and Peter Bailis, Stanford University

Using Online Learning to Improve Resource Efficiency in Interactive Cloud Microservices
Christina Delimitrou, Cornell University

An Energy Modeling Tool for Designing Efficient Hardware for Deep Neural Networks
Vivienne Sze, MIT

Architecting HW Systems for Deep Reinforcement Learning
Michael Taylor, University of Washington

Synthesising Neural Networks on FPGAs with L IFT
Christophe Dubach and Aaron Smith, The University of Edinburgh

A Drop-in Upgradable Near-Data Processing Architecture for Machine Learning Applications in Heterogeneous Computers
Hung-Wei Tseng, North Carolina State University

DIME: A Dynamic Resource-Driven Optimal Scheduling Infrastructure for ML on the Heterogeneous Edge Platforms
Weisong Shi, Wayne State University

Elastic Distributed Machine Learning
Shivaram Venkataraman, University of Wisconsin, Madison