TY - GEN
T1 - Applying autonomic principles for workload management in multi-core systems on chip
AU - Zeppenfeld, Johannes
AU - Herkersdorf, Andreas
PY - 2011
Y1 - 2011
N2 - This paper explores various possibilities for autonomic enhancements to a multi-core network processor system on chip. Based on the autonomic system on chip paradigm, it is shown how monitors can be added to quantify the operating state of a typical processor core, whereupon a learning classifier system evaluator can determine appropriate actions to be performed in order to optimize the frequency and task distribution across the system. A hardware prototype is used to demonstrate the feasibility of autonomic concepts for dynamic component parameterization and task management at run time.
AB - This paper explores various possibilities for autonomic enhancements to a multi-core network processor system on chip. Based on the autonomic system on chip paradigm, it is shown how monitors can be added to quantify the operating state of a typical processor core, whereupon a learning classifier system evaluator can determine appropriate actions to be performed in order to optimize the frequency and task distribution across the system. A hardware prototype is used to demonstrate the feasibility of autonomic concepts for dynamic component parameterization and task management at run time.
KW - autonomic
KW - multi-core
KW - system-on-chip
UR - http://www.scopus.com/inward/record.url?scp=79960162552&partnerID=8YFLogxK
U2 - 10.1145/1998582.1998586
DO - 10.1145/1998582.1998586
M3 - Conference contribution
AN - SCOPUS:79960162552
SN - 9781450306072
T3 - Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
SP - 3
EP - 10
BT - Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
T2 - 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
Y2 - 14 June 2011 through 18 June 2011
ER -