HEAL-WEAR: an Ultra-Low Power Heterogeneous System for Bio-Signal Analysis

Personalized healthcare devices enable low-cost, unobtrusive and long-term acquisition of clinically-relevant biosignals. These appliances, termed Wireless Body Sensor Nodes (WBSNs), are fostering a revolution in health monitoring for patients affected by chronic ailments. Nowadays, WBSNs often embed complex digital processing routines, which must be performed within an extremely tight energy budget. Addressing this challenge, in this paper we introduce a novel computing architecture devoted to the ultra-low power analysis of biosignals. Its heterogeneous structure comprises multiple processors interfaced with a shared acceleration resource, implemented as a Coarse Grained Reconfigurable Array (CGRA). The CGRA mesh effectively supports the execution of the intensive loops that characterize bio-signal analysis applications, while requiring a low reconfiguration overhead. Moreover, both the processors and the reconfigurable fabric feature Single-Instruction / Multiple- Data (SIMD) execution modes, which increase efficiency when multiple data streams are concurrently processed. The run-time behavior on the system is orchestrated by a light-weight hardware mechanism, which concurrently synchronizes processors for SIMD execution and regulates access to the reconfigurable accelerator. By jointly leveraging run-time reconfiguration and SIMD execution, the illustrated heterogeneous system achieves, when executing complex bio-signal analysis applications, speedups of up to 11.3x on the considered kernels and up to 37.2% overall energy savings, with respect to an ultra-low power multicore platform which does not feature CGRA acceleration

Speed-up run-time reconfiguration implementation on FPGAs

International audienceReconfigurable computing is certainly one of the most important emerging research topics over the last few years, in the field of digital processing architectures. The introduction of run-time reconfiguration (RTR) on FPGAs requires appropriate design flows and methodologies to fully exploit this new functionality. For that purpose we present an automatic design generation methodology for heterogeneous architectures based on Network on Chip (NoC) and FPGAs that eases and speed-up RTR implementation. We focus on how to take into account specificities of partially reconfigurable components during the design generation steps. This method automatically generates designs for both fixed and partially reconfigurable parts of a FPGA with automaticmanagement of the reconfiguration process. Furthermore this automatic design generation enables reconfiguration pre-fetching techniques to minimize reconfiguration latency and buffer merging techniques to minimize memory requirements of the generated design. This concept has been applied to different wireless access schemes, based on a combination of OFDM and CDMA techniques. The implementation example illustrates the benefits of the proposed design methodology