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Fast and predictable non-volatile data memory for real-time embedded systems

Bazzaz, M ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1109/TC.2020.2988261
  3. Publisher: IEEE Computer Society , 2020
  4. Abstract:
  5. Energy consumption and predictability are two important constraints in designing real-time embedded systems and one of the recently proposed solutions for the energy consumption problem is the use of non-volatile memories due to their lower leakage power consumption. Furthermore, because of their non-volatile nature, the use of these memories helps normally-off computing and energy harvesting systems. However, the write access latency of non-volatile memories is considerably more than that of SRAM which can decrease the performance and predictability of the system. We present a predictable non-volatile data memory for real-time embedded systems which improves both worst-case execution time (WCET) and performance of the system using a hybrid hardware-software solution. As part of this solution, we add a special write buffer to the memory controller and adopt a multi-bank memory configuration which improves the overall latency of write operations. We also present a new low-overhead software-based optimization technique that makes the proposed system more predictable. Furthermore, we present the WCET analysis algorithm which can be used to estimate the WCET of applications during the design time. The results show that compared to a hybrid SRAM-NVM architecture, the proposed solution improves the WCET and performance by 33% and 47%, respectively. IEEE
  6. Keywords:
  7. Memory management ; Non-volatile memories ; Power management ; Energy harvesting ; Energy utilization ; Integrated circuit design ; Static random access storage ; Energy consumption problems ; Energy harvesting systems ; Leakage power consumption ; Multi-bank memory ; Non-volatile memory ; Optimization techniques ; Real-time embedded systems ; Worst-case execution time ; Real time systems
  8. Source: IEEE Transactions on Computers ; 2020
  9. URL: https://ieeexplore.ieee.org/document/9072321