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Modeling the Power Consumption of Function-Level Code Relocation for Low-Power Embedded Systems
- Title
- Modeling the Power Consumption of Function-Level Code Relocation for Low-Power Embedded Systems
- Authors
- Choi, Hayeon; Koo, Youngkyoung; Park, Sangsoo
- Ewha Authors
- 박상수
- SCOPUS Author ID
- 박상수
- Issue Date
- 2019
- Journal Title
- APPLIED SCIENCES-BASEL
- ISSN
- 2076-3417
- Citation
- APPLIED SCIENCES-BASEL vol. 9, no. 11
- Keywords
- function-level code relocation; prior relocation-scoring; source code insertion; code profiling; low-power; embedded systems
- Publisher
- MDPI
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- Abstract
- The problems associated with the battery life of embedded systems were addressed by focusing on memory components that are heterogeneous and are known to meaningfully affect the power consumption and have not been fully exploited thus far. Our study establishes a model that predicts and orders the efficiency of function-level code relocation. This is based on extensive code profiling that was performed on an actual system to discover the impact and was achieved by using function-level code relocation between the different types of memory, i.e., flash memory and static RAM, to reduce the power consumption. This was accomplished by grouping the assembly instructions to evaluate the distinctive power reduction efficiency depending on function code placement. As a result of the profiling, the efficiency of the function-level code relocation was the lowest at 11.517% for the branch and control groups and the highest at 12.623% for the data processing group. Further, we propose a prior relocation-scoring model to estimate the effective relocation order among functions in a program. To demonstrate the effectiveness of the proposed model, benchmarks in the MiBench benchmark suite were selected as case studies. The experimental results are consistent in terms of the scored outputs produced by the proposed model and measured power reduction efficiencies.
- DOI
- 10.3390/app9112354
- Appears in Collections:
- 인공지능대학 > 컴퓨터공학과 > Journal papers
- Files in This Item:
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Modeling the Power Consumption.pdf(2.14 MB)
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