3 citations · 9 across the 11 of their papers we have counts for
11 papers
NPS: A Framework for Accurate Program Sampling Using Graph Neural Network
Yuanwei Fang, Zihao Liu, Yanheng Lu +7
With the end of Moore's Law, there is a growing demand for rapid architectural innovations in modern processors, such as RISC-V custom extensions, to continue performance scaling.…
Gamora: Graph Learning based Symbolic Reasoning for Large-Scale Boolean Networks
Nan Wu, Yingjie Li, Cong Hao +3
Reasoning high-level abstractions from bit-blasted Boolean networks (BNs) such as gate-level netlists can significantly benefit functional verification, logic minimization, datapat…
High-Resolution GAN Inversion for Degraded Images in Large Diverse Datasets
Yanbo Wang, Chuming Lin, Donghao Luo +3
The last decades are marked by massive and diverse image data, which shows increasingly high resolution and quality. However, some images we obtained may be corrupted, affecting th…
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…
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…
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…