DocumentCode :
3588755
Title :
Paraio: A scalable network I/O framework for many-core systems
Author :
Ping Song ; Yi Liu ; Chi Liu ; Depei Qian ; Qinfen Hao
Author_Institution :
Beijing Key Lab. of Network Technol., Beihang Univ., Beijing, China
fYear :
2014
Firstpage :
1011
Lastpage :
1016
Abstract :
Many high-performance networked applications are designed using the event-driven paradigm. In many-core era, hundreds or even thousands of processor cores can be utilized to serve more clients. However, data race and load imbalance in current event-driven hybrid models will be a key bottleneck which challenges developers to fully exploit many-core resources to develop high-performance networked applications. In this paper, we extend the symmetric multi-thread event-driven model and present Paraio, a scalable network I/O framework to improve performance of networked applications such as web servers and software-defined network (SDN) controllers. In order to maximize the degree of parallelism in the event-based application execution, Paraio features the shared-data marking method that divides the event-processing logic and marks event handlers from the essential shared data perspective. In Paraio runtime, workloads are balanced among threads by an efficient work stealing, and new connection is allocated according to threads´ load to obtain a fast response. Evaluation on web server and SDN controller, shows that Paraio applications with work stealing achieve better performance and scalability.
Keywords :
multi-threading; multiprocessing systems; resource allocation; software defined networking; Paraio; SDN controllers; Web servers; data race; event-based application execution; event-driven hybrid models; event-driven paradigm; event-processing logic; high-performance networked applications; load imbalance; many-core resources; many-core systems; parallelism; processor cores; scalable network I/O framework; shared-data marking method; software-defined network controllers; symmetric multithread event-driven model; Instruction sets; Load modeling; Message systems; Runtime; Throughput; Web servers; data race; event-driven model; many-core system; multithread architecture; work stealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Systems (ICPADS), 2014 20th IEEE International Conference on
Type :
conf
DOI :
10.1109/PADSW.2014.7097924
Filename :
7097924
Link To Document :
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