Low-power processor architecture exploration for online biomedical signal analysis

In this study, we explore sequential and parallel processing architectures, utilizing a custom ultra-low-power (ULP) processing core, to extend the lifetime of health monitoring systems, where slow biosignal events and highly parallel computations exist. To this end, a singleand a multi-core architecture are proposed and compared. The single-core architecture is composed of one ULP processing core, an instruction memory (IM) and a data memory (DM), while the multicore architecture consists of several ULP processing cores, 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/performance trade-offs for different target workloads of online biomedical signal analysis, while exploiting near threshold com2 A. Y. Dogan, J. Constantin, D. Atienza, A. Burg, L. Benini puting. The results show that with respect to the single-core architecture, the multi-core solution consumes 62% less power for high computation requirements (167MOps/s), while consuming 46% more power for extremely low computation needs when the power consumption is dominated by leakage. Additionally, we show that our proposed ULP processing core, using a simplified instruction set architecture (ISA), achieves energy savings of 54% compared to a reference microcontroller ISA (PIC24).