Goal-Driven Autonomy for Efficient On-chip Resource Management: Transforming Objectives to Goals
Elham Shamsa1,a, Anil Kanduri1,b, Amir M. Rahmani2,3,d, Pasi Liljeberg1,c, Axel Jantsch3 and Nikil Dutt2,e
1University of Turku, Turku, Finland
aelsham@utu.fi
bspakan@utu.fi
cpakrli@utu.fi
2University of California, Irvine, USA
da.rahmani@uci.edu
edutt@uci.edu
3Institute of Computer Technology, TU Wien, Vienna, Austria
axel.jantsch@tuwien.ac.at
ABSTRACT
Run-time resource allocation of heterogeneous multi-core systems is challenging with varying workloads and limited power and energy budgets. User interaction within these systems changes the performance requirements, often conflicting with concurrent applications’ objective and system constraints. Current resource allocation approaches focus on optimizing fixed objective, ignoring the variation in system and applications’ objective at run-time. For an efficient resource allocation, the system has to operate autonomously by formulating a hierarchy of goals. We present goal-driven autonomy (GDA) for on-chip resource allocation decisions, which allows systems to generate and prioritize goals in response to the workload and system dynamic variation. We implemented a proof-of-concept resource management framework that integrates the proposed goal management control to meet power, performance and user requirements simultaneously. Experimental results on an Exynos platform containing ARM’s big.LITTLE-based heterogeneous multi-processor (HMP) show the effectiveness of GDA in efficient resource allocation in comparison with existing fixed objective policies.
Keywords: Goal-Driven Autonomy, Autonomous and Self-Aware Systems, On-chip Resource allocation, Heterogeneous Multi-core Systems.
