Dogan, Ahmed YasirBraojos Lopez, RubenConstantin, Jeremy Hugues-FelixAnsaloni, GiovanniBurg, Andreas PeterAtienza Alonso, David2013-01-082013-01-082013-01-08201310.7873/DATE.2013.090https://infoscience.epfl.ch/handle/20.500.14299/87696Embedded biosignal analysis involves a considerable amount of parallel computations, which can be exploited by employing low-voltage and ultra-low-power (ULP) parallel computing architectures. By allowing data and instruction broadcasting, single instruction multiple data (SIMD) processing paradigm enables considerable power savings and application speedup, in turn allowing for a lower voltage supply for a given workload. The state-of-the-art multi-core architectures for biosignal analysis however lack a bare, yet smart, synchronization technique among the cores, allowing lockstep execution of algorithm parts that can be performed using the SIMD, even in the presence of data-dependent execution flows. In this paper, we propose a lightweight synchronization technique to enhance an ULP multi-core processor, resulting in improved energy efficiency through lockstep SIMD execution. Our results show that the proposed improvements accomplish tangible power savings, up to 64% for an 8-core system operating at a workload of 89 MOps/s while exploiting voltage scaling.single instruction multiple dataSIMDdata level parallelismmulti-core architecturesparallel computinghardware synchronizerultra-low-powertext::conference output::conference proceedings::conference paper