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Performance Evaluation and Improvement of RTM-based Scratchpad Memory in Embedded Systems

Lotfi Takami, Alireza | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50289 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Ejlali, Alireza
  7. Abstract:
  8. Embedded systems usually are real-time, it means they have timing constraint and should finish their tasks before a deadline. Besides, most of the embedded systems have an energy consumption constraint, because the source of their energy is battery. Due to these two requirements, embedded systems often employ software-controlled Scratch Pad Memory (SPM) instead of hardware-controlled cache as their on-chip memory. SPM is a software-controlled on-chip memory, has been widely adopted in many embedded systems due to its smaller area, lower power consumption and better time predictability. With increasing the number of CMOS transistors along with density, leakage power consumption is becoming a critical issue for memory components. So, it is necessary to take advantage of the ultralow leakage power and high density of NVMs. Racetrack Memory (RTM) has considerable advantages over other NVMs. So, in this paper, we propose a low energy and time efficient data allocation algorithm on area efficient hybrid on-chip memory consisting of SRAM and RTM. Most capacity of the proposed hybrid on-chip memory consists of RTM but RTM has shift and write energy/time overhead problems. So, we use small SRAM alongside with the RTM to avoid write energy/time overhead, and try to decrease shift operations. Experimental results show that the proposed techniques can reduce energy consumption and Actual Execution Time (ACET) of program, respectively about 60% compared with hybrid SRAM-STT-RAM and pure RTM on-chip memory while WCET of the program will increase less than 1% compared with pure SRAM
  9. Keywords:
  10. Real Time ; Scratch Pad Memory (SPM) ; Memory Management ; Embedded System ; Racetrack Memory (RTM)

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