A Review on Task Performance Prediction in Multi-core Based Systems

• Published in: 2011 IEEE 11th International Conference on Computer and Information Technology pp. 615 - 620
• Main Authors: Pinel, F., Pecero, J. E., Bouvry, P., Khan, S. U.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-08-2011
• Subjects: Computational modeling; energy-efficiency; Instruction sets; Operating systems; performance of system; Predictive models; Processor scheduling; Runtime; scalable architectures; task profiling
• ISBN: 1457703831; 9781457703836
• DOI: 10.1109/CIT.2011.107

Operators of data centers are faced with the challenging goal of hosting applications that meet agreed service levels, at minimal operating costs. A significant part of these costs is energy related. Successfully reaching this goal requires optimal task-to-machine assignments. This activity relies on accurate energy and performance prediction. Widespread use of multi-core, multi-processor machines complicate past prediction methods. Therefore, this paper suggests to revisit task profiling, a method based on observations of actual task execution. As a first step in this direction, this paper reviews methods for task profiling, which account for the contention present in multi-core processors.