Journal of Xidian University ›› 2021, Vol. 48 ›› Issue (6): 57-66.doi: 10.19665/j.issn1001-2400.2021.06.008

• Special Issue:Key Technology of Architecture and Software for Intelligent Embedded Systems • Previous Articles     Next Articles

Analysis of the relationship between the performance of the BC and the format of the graph data

JIANG Lin1(),FENG Ru1(),DENG Junyong2(),LI Yuancheng1()   

  1. 1. School of Computer Science and Technology,Xi’an University of Science and Technology,Xi’an 710600,China
    2. School of Electronic Engineering,Xi’an University of Posts and Telecommunications,Xi’an 710121,China
  • Received:2021-08-16 Online:2021-12-20 Published:2022-02-24

Abstract:

The data compression format in graph computing is one of the key influencing factors of graph algorithm memory access efficiency and performance.Based on this,this paper focuses on how the BC (Betweenness Centrality) algorithm selects the appropriate compression format according to performance requirements to improve the performance of the graph computing system.The hardware performance counter on the Skylake Xeon(R) Platinum 8164 processor is used to analyze different data,with acollection of five compression formats of COO,CSC,CSR,DCSC and CSCI adopted for performance evaluation and analysis.Performance evaluation indicators include execution time,calculation volume,data movement volume,and power consumption.The evaluation results show that when hardware resources are limited,the CSR compression format performs best when processing the traversal-centric BC algorithm,which can effectively reduce the program execution time,data movement,and power consumption.Using the CSC compression format can effectively reduce the Cache miss rate and lead to a better use of data locality.Using the DCSC compression format can improve the graph data storage efficiency when considering memory usage.Using the CSCI compression format has certain advantages in the data parallelism of hardware accelerators,but for general-purpose processors the graph application is not ideal.The COO compression format is relatively poor in improving the performance of graph computing applications.Analytical results provide a basis for how the BC algorithm selects preprocessing methods according to different performance requirements

Key words: graph processing, compression format, betweenness centrality, performance analysis

CLC Number: 

  • TP302.7