The energy case for graph processing on hybrid CPU and GPU systems
- 17 November 2013
- conference paper
- conference paper
- Published by Association for Computing Machinery (ACM) in Proceedings of the 3rd Workshop on Irregular Applications Architectures and Algorithms - IA^3 '13
Abstract
This paper investigates the power, energy, and performance characteristics of large-scale graph processing on hybrid (i.e., CPU and GPU) single-node systems. Graph processing can be accelerated on hybrid systems by properly mapping the graph-layout to processing units, such that the algorithmic tasks exercise each of the units where they perform best. However, the GPUs have much higher Thermal Design Power (TDP), thus their impact on the overall energy consumption is unclear. Our evaluation using large real-world graphs and synthetic graphs as large as 1 billion vertices and 16 billion edges shows that a hybrid system is efficient in terms of both time-to-solution and energy.Keywords
Other Versions
This publication has 18 references indexed in Scilit:
- TurboGraphPublished by Association for Computing Machinery (ACM) ,2013
- On Graphs, GPUs, and Blind Dating: A Workload to Processor Matchmaking QuestPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- A yoke of oxen and a thousand chickens for heavy lifting graph processingPublished by Association for Computing Machinery (ACM) ,2012
- Fast and Efficient Graph Traversal Algorithm for CPUs: Maximizing Single-Node EfficiencyPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Nobody ever got fired for using Hadoop on a clusterPublished by Association for Computing Machinery (ACM) ,2012
- Efficient Parallel Graph Exploration on Multi-Core CPU and GPUPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- What is Twitter, a social network or a news media?Published by Association for Computing Machinery (ACM) ,2010
- A large time-aware web graphACM SIGIR Forum, 2008
- Structure and evolution of online social networksPublished by Association for Computing Machinery (ACM) ,2006
- A bridging model for parallel computationCommunications of the ACM, 1990