88 citations · 135 across the 4 of their papers we have counts for
4 papers
NNSmith: Generating Diverse and Valid Test Cases for Deep Learning Compilers
Jiawei Liu, Jinkun Lin, Fabian Ruffy +4
Deep-learning (DL) compilers such as TVM and TensorRT are increasingly being used to optimize deep neural network (DNN) models to meet performance, resource utilization and other r…
I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization
Tong Geng, Chunshu Wu, Yongan Zhang +6
Graph Convolutional Networks (GCNs) have drawn tremendous attention in the past three years. Compared with other deep learning modalities, high-performance hardware acceleration of…
ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing
Cheng Tan, Chenhao Xie, Tong Geng +4
The next generation HPC and data centers are likely to be reconfigurable and data-centric due to the trend of hardware specialization and the emergence of data-driven applications.…
Synergy: A HW/SW Framework for High Throughput CNNs on Embedded Heterogeneous SoC
Guanwen Zhong, Akshat Dubey, Tan Cheng +1
Convolutional Neural Networks (CNN) have been widely deployed in diverse application domains. There has been significant progress in accelerating both their training and inference…