This study presents a single-core and a multi-core processor architecture for health monitoring systems where slow biosignal events and highly parallel computations exist. The single-core architecture is composed of a processing core (PC), an instruction memory (IM) and a data memory (DM), while the multi-core architecture consists of PCs, individual IMs for each core, a shared DM and an interconnection crossbar between the cores and the DM. These architectures are compared with respect to power vs performance trade-offs for a multi-lead electrocardiogram signal conditioning application exploiting near threshold computing. The results show that the multi-core solution consumes 66% less power for high computation requirements (50.1 MOps/s), whereas 10.4% more power for low computation needs (681 kOps/s).
Power/performance exploration of single-core and multi-core processor approaches for biomedical signal processing / A. Dogan; D. Atienza; A. Burg; I. Loi; L. Benini. - STAMPA. - (2011), pp. 102-111. (Intervento presentato al convegno PATMOS'11 Proceedings of the 21st international conference on Integrated circuit and system design: power and timing modeling, optimization, and simulation tenutosi a Madrid, Spain nel September 26-29, 2011) [10.1007/978-3-642-24154-3_11].
Power/performance exploration of single-core and multi-core processor approaches for biomedical signal processing
LOI, IGOR;BENINI, LUCA
2011
Abstract
This study presents a single-core and a multi-core processor architecture for health monitoring systems where slow biosignal events and highly parallel computations exist. The single-core architecture is composed of a processing core (PC), an instruction memory (IM) and a data memory (DM), while the multi-core architecture consists of PCs, individual IMs for each core, a shared DM and an interconnection crossbar between the cores and the DM. These architectures are compared with respect to power vs performance trade-offs for a multi-lead electrocardiogram signal conditioning application exploiting near threshold computing. The results show that the multi-core solution consumes 66% less power for high computation requirements (50.1 MOps/s), whereas 10.4% more power for low computation needs (681 kOps/s).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
