498 citations · 2.5k across the 114 of their papers we have counts for
4 papers · 1 filter
CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks
Runbin Shi, Peiyan Dong, Tong Geng +6
Recurrent neural networks (RNNs) have been widely adopted in temporal sequence analysis, where realtime performance is often in demand. However, RNNs suffer from heavy computationa…
Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs
Caiwen Ding, Ao Ren, Geng Yuan +5
Both industry and academia have extensively investigated hardware accelerations. In this work, to address the increasing demands in computational capability and memory requirement,…
Model-Free Control for Distributed Stream Data Processing using Deep Reinforcement Learning
Teng Li, Zhiyuan Xu, Jian Tang +1
In this paper, we focus on general-purpose Distributed Stream Data Processing Systems (DSDPSs), which deal with processing of unbounded streams of continuous data at scale distribu…
A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning
Ning Liu, Zhe Li, Zhiyuan Xu +5
Automatic decision-making approaches, such as reinforcement learning (RL), have been applied to (partially) solve the resource allocation problem adaptively in the cloud computing…