Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors
Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
Barcelona Supercomputing Center
Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
2019
Voltage underscaling below the nominal level is an effective solution for improving energy efficiency in digital circuits, e.g., Field Programmable Gate Arrays (FPGAs). However, further undervolting below a safe voltage level and without accompanying frequency scaling leads to timing related faults, potentially undermining the energy savings. Through experimental voltage underscaling studies on commercial FPGAs, we observed that the rate of these faults exponentially increases for on-chip memories, or Block RAMs (BRAMs). To mitigate these faults, we evaluated the efficiency of the built-in Error-Correction Code (ECC) and observed that more than 90 % of the faults are correctable and further 7 % are detectable (but not correctable). This efficiency is the result of the single-bit type of these faults, which are then effectively covered by the Single-Error Correction and Double-Error Detection (SECDED) design of the built-in ECC. Finally, motivated by the above experimental observations, we evaluated an FPGA-based Neural Network (NN) accelerator under low-voltage operations, while built-in ECC is leveraged to mitigate undervolting faults and thus, prevent NN significant accuracy loss. In consequence, we achieve 40 % of the BRAM power saving through undervolting below the minimum safe voltage level, with a negligible NN accuracy loss, thanks to the substantial fault coverage by the built-in ECC.
The research leading to these results hasreceived funding from the European Union’s Horizon 2020 Programme under the LEGaTO Project (www.legato-project.eu),grantagreement n 780681.
Peer Reviewed
Postprint (author's final draft)
Conference report
English
Àrees temàtiques de la UPC::Enginyeria electrònica::Microelectrònica::Circuits integrats; Field programmable gate arrays; Error-correcting codes (Information theory); Logic design; Circuit faults; Random access memory; Power demand; Artificial neural networks; Computer crashes; Matrius de portes programables per l'usuari; Codis correctors d'errors (Teoria de la informació); Estructura lògica
Institute of Electrical and Electronics Engineers (IEEE)
https://ieeexplore.ieee.org/document/8671543/
info:eu-repo/grantAgreement/EC/H2020/780681/EU/Low Energy Toolset for Heterogeneous Computing/LEGaTO
Open Access
E-prints [72263]