activity
20202023
most citedAutoComm: A Framework for Enabling Efficient Communication in Distributed Quantum Programs

3 citations · 9 across the 11 of their papers we have counts for

collaborators

8 papers

cs.CV2022

Attentive pooling for Group Activity Recognition

Ding Li, Yuan Xie, Wensheng Zhang +2

In group activity recognition, hierarchical framework is widely adopted to represent the relationships between individuals and their corresponding group, and has achieved promising…

cs.AR2022

Characterizing and Understanding HGNNs on GPUs

Mingyu Yan, Mo Zou, Xiaocheng Yang +4

Heterogeneous graph neural networks (HGNNs) deliver powerful capacity in heterogeneous graph representation learning. The execution of HGNNs is usually accelerated by GPUs. Therefo…

cs.DC2022

Predicting the Output Structure of Sparse Matrix Multiplication with Sampled Compression Ratio

Zhaoyang Du, Yijin Guan, Tianchan Guan +7

Sparse general matrix multiplication (SpGEMM) is a fundamental building block in numerous scientific applications. One critical task of SpGEMM is to compute or predict the structur…

quant-ph20223 cited

AutoComm: A Framework for Enabling Efficient Communication in Distributed Quantum Programs

Anbang Wu, Hezi Zhang, Gushu Li +3

Distributed quantum computing (DQC) is a promising approach to extending the computational power of near-term quantum devices. However, the non-local quantum communication between…

cs.AR2022

Multi-node Acceleration for Large-scale GCNs

Gongjian Sun, Mingyu Yan, Duo Wang +5

Limited by the memory capacity and compute power, singe-node graph convolutional neural network (GCN) accelerators cannot complete the execution of GCNs within a reasonable amount…

cs.NE2021

Compact Multi-level Sparse Neural Networks with Input Independent Dynamic Rerouting

Minghai Qin, Tianyun Zhang, Fei Sun +4

Deep neural networks (DNNs) have shown to provide superb performance in many real life applications, but their large computation cost and storage requirement have prevented them fr…