TY - GEN
T1 - Trillion-scale graph processing simulation based on top-down graph upscaling
AU - Park, Himchan
AU - Xiong, Jinjun
AU - Kim, Min Soo
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4
Y1 - 2021/4
N2 - As the number of graph applications increases rapidly in many domains, new graph algorithms (or queries) have become more important than ever before. The current two-step approach to develop and test a graph algorithm is very expensive for trillion-scale graphs required in many industrial applications. In this paper, we propose a concept of graph processing simulation, a single-step approach that generates a graph and processes a graph algorithm simultaneously. It consists of a top-down graph upscaling method called V-Upscaler and a graph processing simulation method following the vertex-centric GAS model called T-GPS. Users can develop a graph algorithm and check its correctness and performance conveniently and cost-efficiently even for trillion-scale graphs. Through extensive experiments, we have demonstrated that our single-step approach of V-Upscaler and T-GPS significantly outperforms the conventional two-step approach, although ours uses only a single machine, while the conventional one uses a cluster of eleven machines.
AB - As the number of graph applications increases rapidly in many domains, new graph algorithms (or queries) have become more important than ever before. The current two-step approach to develop and test a graph algorithm is very expensive for trillion-scale graphs required in many industrial applications. In this paper, we propose a concept of graph processing simulation, a single-step approach that generates a graph and processes a graph algorithm simultaneously. It consists of a top-down graph upscaling method called V-Upscaler and a graph processing simulation method following the vertex-centric GAS model called T-GPS. Users can develop a graph algorithm and check its correctness and performance conveniently and cost-efficiently even for trillion-scale graphs. Through extensive experiments, we have demonstrated that our single-step approach of V-Upscaler and T-GPS significantly outperforms the conventional two-step approach, although ours uses only a single machine, while the conventional one uses a cluster of eleven machines.
UR - https://www.scopus.com/pages/publications/85112865927
U2 - 10.1109/ICDE51399.2021.00134
DO - 10.1109/ICDE51399.2021.00134
M3 - Conference contribution
AN - SCOPUS:85112865927
T3 - Proceedings - International Conference on Data Engineering
SP - 1512
EP - 1523
BT - Proceedings - 2021 IEEE 37th International Conference on Data Engineering, ICDE 2021
PB - IEEE Computer Society
T2 - 37th IEEE International Conference on Data Engineering, ICDE 2021
Y2 - 19 April 2021 through 22 April 2021
ER -