Title
Scalable Parallel Distributed Coprocessor System for Graph Searching Problems with Massive Data
Abstract
AbstractThe Internet applications, such as network searching, electronic commerce, and modern medical applications, produce and process massive data. Considerable data parallelism exists in computation processes of data-intensive applications. A traversal algorithm, breadth-first search (BFS), is fundamental in many graph processing applications and metrics when a graph grows in scale. A variety of scientific programming methods have been proposed for accelerating and parallelizing BFS because of the poor temporal and spatial locality caused by inherent irregular memory access patterns. However, new parallel hardware could provide better improvement for scientific methods. To address small-world graph problems, we propose a scalable and novel field-programmable gate array-based heterogeneous multicore system for scientific programming. The core is multithread for streaming processing. And the communication network InfiniBand is adopted for scalability. We design a binary search algorithm to address mapping to unify all processor addresses. Within the limits permitted by the Graph500 test bench after 1D parallel hybrid BFS algorithm testing, our 8-core and 8-thread-per-core system achieved superior performance and efficiency compared with the prior work under the same degree of parallelism. Our system is efficient not as a special acceleration unit but as a processor platform that deals with graph searching applications.
Year
DOI
Venue
2017
10.1155/2017/1496104
Periodicals
Field
DocType
Volume
Tree traversal,Degree of parallelism,Computer science,Breadth-first search,Parallel computing,Data parallelism,Binary search algorithm,Coprocessor,Multi-core processor,Scalability
Journal
2017
Issue
ISSN
Citations 
1
1058-9244
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Wanrong Huang112.39
Xiaodong Yi25920.16
Yichun Sun300.68
Yingwen Liu400.34
Shuai Ye500.34
Hengzhu Liu68623.28