From the 1 of 10 linked papers with an AI index.
6 citations · 13 across the 6 of their papers we have counts for
10 papers
Coherence in Control: Bridging Many-Core Mapping and Routing through Cost Unification
Guochu Xiong, Xiangzhong Luo, Weichen Liu
The rapid growth of data-intensive applications increases communication demands in many-core systems, where cache coherence, while essential for correct communication and data cons…
Mapping Without Graphs: Learning Coherence Traffic for Task Placement
Guochu Xiong, Tianrui Ma, Weichen Liu
Cache coherence is essential for communication in many-core Network-on-Chip (NoC)-based systems. As application scale and complexity increase, efficiently managing communication be…
Towards Efficient Convolutional Neural Network for Embedded Hardware via Multi-Dimensional Pruning
Hao Kong, Di Liu, Xiangzhong Luo +5
The paper introduces TECO, a framework that jointly prunes depth, width, and input resolution of convolutional neural networks to improve speed and resource usage on embedded devic…
EvoLP: Self-Evolving Latency Predictor for Model Compression in Real-Time Edge Systems
Shuo Huai, Hao Kong, Shiqing Li +5
Edge devices are increasingly utilized for deploying deep learning applications on embedded systems. The real-time nature of many applications and the limited resources of edge dev…
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation
Shuo Huai, Hao Kong, Xiangzhong Luo +5
Crossbar-based In-Memory Processing (IMP) accelerators achieve high-speed, low-power computing for deep neural networks (DNNs), but face three obstacles. First, floating-point (FP)…
FedTR: Federated Learning Framework with Transfer Learning for Industrial Visual Inspection
Vikash Sathiamoorthy, Shuo Huai, Hao Kong +7
Federated learning (FL) is a collaborative learning scheme to train deep learning models, where collaborating parties can consolidate their models without sharing local data with o…