Virtualization is a key enabler technology for cloud computing. It allows applications to share computing, memory, storage, and network resources. However, physical resources are not standalone and the server infrastructure is not homogeneous. The CPU cores are commonly connected to the shared memory, caches, and computational units. As a result, the performance of cloud applications can be greatly affected if, while being executed at different computing cores, they compete for the same shared cache or network resource. The performance degradation can be as high as 50%. In this work we present a methodology which predicts the performance problems of cloud applications during their concurrent execution by looking at the hardware performance counters collected during their standalone execution. The proposed methodology fosters design of novel solutions for efficient resource allocation and scheduling.

Profiling Cloud Applications with Hardware Performance Counters

Kandalintsev, Alexandre;Lo Cigno, Renato Antonio;
2014-01-01

Abstract

Virtualization is a key enabler technology for cloud computing. It allows applications to share computing, memory, storage, and network resources. However, physical resources are not standalone and the server infrastructure is not homogeneous. The CPU cores are commonly connected to the shared memory, caches, and computational units. As a result, the performance of cloud applications can be greatly affected if, while being executed at different computing cores, they compete for the same shared cache or network resource. The performance degradation can be as high as 50%. In this work we present a methodology which predicts the performance problems of cloud applications during their concurrent execution by looking at the hardware performance counters collected during their standalone execution. The proposed methodology fosters design of novel solutions for efficient resource allocation and scheduling.
2014
KIISE/IEEE 28th International Conference on Information Networking
USA
IEEE
9781479936892
Kandalintsev, Alexandre; Lo Cigno, Renato Antonio; D., Kliazovich; P., Bouvry
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/98032
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