Large-scale graph processing is gaining increasing attentions in many domains. Meanwhile, FPGA provides a power-efficient and highly parallel platform for many applications, and has …
Due to the growing need to process large graph and network datasets created by modern applications, recent years have witnessed a surging interest in developing big graph …
Recent studies show that graph processing systems on a single machine can achieve competitive performance compared with cluster-based graph processing systems. In this …
D Yan, G Guo, MMR Chowdhury… - 2020 IEEE 36th …, 2020 - ieeexplore.ieee.org
Mining from a big graph those subgraphs that satisfy certain conditions is useful in many applications such as community detection and subgraph matching. These problems have a …
Y Zhang, X Liao, H Jin, L He, B He… - … Symposium on High …, 2021 - ieeexplore.ieee.org
Many graph processing systems have been recently developed for many-core processors. However, for iterative graph processing, due to the dependencies between vertices' states …
Y Zhang, X Liao, H Jin, B He, H Liu, L Gu - Proceedings of the Twenty …, 2019 - dl.acm.org
Many systems are recently proposed for large-scale iterative graph analytics on a single machine with GPU accelerators. Despite of many research efforts, for iterative directed graph …
Graph processing is becoming commonplace in many applications to analyze huge datasets. Much of the prior work in this area has assumed I/O devices with considerable …
D Yan, J Cheng, MT Özsu, F Yang, Y Lu, J Lui… - arXiv preprint arXiv …, 2016 - arxiv.org
Pioneered by Google's Pregel, many distributed systems have been developed for large- scale graph analytics. These systems expose the user-friendly" think like a vertex" …
Despite its popularity, SimRank is computationally costly, in both time and space. In particular, its recursive nature poses a great challenge in using modern distributed …