Performance characteristics of Graph500 on large-scale distributed environment

Authors:
Toyotaro Suzumura;Koji Ueno;Hitoshi Sato;Katsuki Fujisawa;Satoshi Matsuoka
Affiliations:
Tokyo Institute of Technology, Japan;Tokyo Institute of Technology, Japan;Tokyo Institute of Technology, Japan;Chuo University, Japan;Tokyo Institute of Technology, Japan
Venue:
IISWC '11 Proceedings of the 2011 IEEE International Symposium on Workload Characterization
Year:
2011

Citing 0
Cited 3

Highly scalable graph search for the Graph500 benchmark

Proceedings of the 21st international symposium on High-Performance Parallel and Distributed Computing
Large-scale energy-efficient graph traversal: a path to efficient data-intensive supercomputing

SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Extreme big data processing in large-scale graph analytics and billion-scale social simulation

Proceedings of the 5th ACM/SPEC international conference on Performance engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

Graph500 is a new benchmark for supercomputers based on large-scale graph analysis, which is becoming an important form of analysis in many real-world applications. Graph algorithms run well on supercomputers with shared memory. For the Linpack-based supercomputer rankings, TOP500 reports that heterogeneous and distributed-memory super-computers with large numbers of GPGPUs are becoming dominant. However, the performance characteristics of large-scale graph analysis benchmarks such as Graph500 on distributed-memory supercomputers have so far received little study. This is the first report of a performance evaluation and analysis for Graph500 on a commodity-processor-based distributed-memory supercomputer. We found that the reference implementation "replicated-csr" based on distributed level-synchronized breadth-first search solves a large free graph problem with 2