70 citations · 183 across the 6 of their papers we have counts for
6 papers
Order-Preserving Key Compression for In-Memory Search Trees
Huanchen Zhang, Xiaoxuan Liu, David G. Andersen +3
We present the High-speed Order-Preserving Encoder (HOPE) for in-memory search trees. HOPE is a fast dictionary-based compressor that encodes arbitrary keys while preserving their…
Accelerating Deep Learning by Focusing on the Biggest Losers
Angela H. Jiang, Daniel L. -K. Wong, Giulio Zhou +8
This paper introduces Selective-Backprop, a technique that accelerates the training of deep neural networks (DNNs) by prioritizing examples with high loss at each iteration. Select…
Scaling Video Analytics on Constrained Edge Nodes
Christopher Canel, Thomas Kim, Giulio Zhou +5
As video camera deployments continue to grow, the need to process large volumes of real-time data strains wide area network infrastructure. When per-camera bandwidth is limited, it…
EDF: Ensemble, Distill, and Fuse for Easy Video Labeling
Giulio Zhou, Subramanya Dulloor, David G. Andersen +1
We present a way to rapidly bootstrap object detection on unseen videos using minimal human annotations. We accomplish this by combining two complementary sources of knowledge (one…
Datacenter RPCs can be General and Fast
Anuj Kalia, Michael Kaminsky, David G. Andersen
It is commonly believed that datacenter networking software must sacrifice generality to attain high performance. The popularity of specialized distributed systems designed specifi…
3LC: Lightweight and Effective Traffic Compression for Distributed Machine Learning
Hyeontaek Lim, David G. Andersen, Michael Kaminsky
The performance and efficiency of distributed machine learning (ML) depends significantly on how long it takes for nodes to exchange state changes. Overly-aggressive attempts to re…