In a context of increasing demands for on-board data processing, insuring reliability under reduced power budget is a serious design challenge for embedded system manufacturers. Particularly, embedded processors in aggressive environments need to be designed with error hardening as a primary goal, not an afterthought. As Register File (RF) is a critical element within the processor pipeline, enhancing RF reliability is mandatory to design fault immune computing systems. This study proposes integer and floating point RF reliability enhancement techniques. Specifically, the authors propose Adjacent Register Hardened RF, a new RF architecture that exploits the adjacent byte-level narrow-width values for hardening integer registers at runtime. Registers are paired together by special switches referred to as joiners and non-utilised bits of each register are exploited to enhance the reliability of its counterpart register. Moreover, they suggest sacrificing the least significant bits of the Mantissa to enhance the reliability of the floating point critical bits, namely, Exponent and Sign bits. The authors’ results show that with a low power budget compared to state of the art techniques, they achieve better results under both normal and highly aggressive operating conditions.

With successive scaling of CMOS technology, power density and cooling costs significantly increase. Consequently, the cooling system of processors can no longer be designed for the worst-case situation in each generation of CMOS technology and there is an essential need for run-time techniques to control the operating temperature. Task scheduling and resource management with respect to thermal constraints are run-time methods used to control the thermal profile of a system. In this study, the authors use Markov Reward Models (MRMs) to model and evaluate a new core thermal management method, which can reduce hotspots and balance the thermal profile of a multi-core system. Although the proposed management method degrades the performance of the system, such as other previously presented methods, it controls the temperature of a die to decrease the temperature variation and hotspots. The proposed approach is assessed on a quad-core system and the experimental results are compared to the results obtained from the proposed MRM to demonstrate the accuracy of the proposed analytical model.

Safety-critical technology rests on optimised and effective testing techniques for every embedded system involved in the equipment. Pattern generator (PG) such as linear feedback shift register (LFSR) is used for fault detection and useful for reliability and online test. This study presents an analysis of the LFSR, using a known automatic test PG (ATPG) test set. Two techniques are undertaken to target difficult-to-detect faults with their respective trade-off analysis. This is achieved using Berlekamp–Massey (BM) algorithm with optimisations to reduce area overhead. The first technique (concatenated) combines all test sets generating a single polynomial that covers complete ATPG set (baseline-C). Improvements are found in Algorithm 1 reducing polynomial size through Xs assignment. The second technique uses non-concatenated test sets and provides a group of LFSRs using BM without including any optimisation (baseline-N). This algorithm is further optimised by selecting full mapping and independent polynomial expressions. Results are generated using 32 benchmarks and 65 nm technology. The concatenated technique provides reductions on area overhead for 90.6% cases with a best case of 57 and 39% means. The remaining 9.4% of cases, non-concatenated technique provides the best reduction of 37 with 1.4% means, whilst achieving 100% test mapping in both cases.