Title
A case for scaling applications to many-core with OS clustering
Abstract
This paper proposes an approach to scaling UNIX-like operating systems for many cores in a backward-compatible way, which still enjoys common wisdom in new operating system designs. The proposed system, called Cerberus, mitigates contention on many shared data structures within OS kernels by clustering multiple commodity operating systems atop a VMM, and providing applications with the traditional shared memory interface. Cerberus extends a traditional VMMwith efficient support for resource sharing and communication among the clustered operating systems. It also routes system calls of an application among operating systems, to provide applications with the illusion of running on a single operating system. We have implemented a prototype system based on Xen/Linux, which runs on an Intel machine with 16 core and an AMD machine with 48 cores. Experiments with an unmodified MapReduce application, dbench, Apache Web Server and Memcached show that, given the nontrivial performance overhead incurred by the virtualization layer, Cerberus achieves up to 1.74X and 4.95X performance speedup compared to native Linux. It also scales better than a single Linux configuration. Profiling results further show that Cerberus wins due to mitigated contention and more efficient use of resources.
Year
DOI
Venue
2011
10.1145/1966445.1966452
EuroSys
Keywords
Field
DocType
multiple commodity operating system,single linux configuration,os clustering,prototype system,proposed system,single operating system,system call,unix-like operating system,amd machine,native linux,new operating system design,shared memory,resource sharing,operating system,scalability,data structure,multicore
Virtualization,Shared memory,Computer science,Real-time computing,Cluster analysis,Shared resource,Multi-core processor,Operating system,Speedup,Web server,Scalability
Conference
Citations 
PageRank 
References 
20
0.87
18
Authors
5
Name
Order
Citations
PageRank
Xiang Song11157.19
Haibo Chen21749123.40
Rong Chen358630.22
Yuanxuan Wang4200.87
Binyu Zang598462.75