ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2019, Vol. 56 ›› Issue (8): 1772-1782.doi: 10.7544/issn1000-1239.2019.20170694

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SSD Power Modeling Method Based on the Gradient of Energy Consumption

Sun Jian1,2, Li Zhanhuai2, Li Qiang1, Zhang Xiao2, Zhao Xiaonan2   

  1. 1(School of Computer Science and Engineering, North Minzu University, Yinchuan 750021);2(School of Computer Science and Engineering, Northwestern Polytechnical of University, Xi’an 710129)
  • Online:2019-08-01

Abstract: In recent years, flash memory chips (NANDFLASH) production technology has been improved, the storage capacity and data throughput enhances unceasingly. NAND flash SSDs have become the preferred storage device in both consumer electronics and datacenters. Flash has superior random access characteristics to speed up many applications and consumes less power than HDDs. Flash chips has become a mainstream storage components in the field of mobile terminal. But with the reduce of the flash memory cost, its application range is gradually extended to mass data storage system. In view of the lower forecast accuracy for flash drives energy consumption in the storage system. We propose a gradient-based SSD power modeling method that estimates the power consumption of storage workloads, and it effectively enhances the energy consumption prediction precision. This method is based on the hierarchical structure and working principle of NAND flash chips, and analyzes the energy consumption in the process of reading and writing. we build energy consumption gradient list with alternation and parallelism operation, and predict energy consumption of SSD. This kind of modeling method will not bring additional performance overhead to the system. The experimental results show the prediction accuracy of gradient-based modeling method has been improved significantly compared with the traditional linear model.

Key words: flash memory, non-volatile memory, storage system, energy-consuming model, energy efficient

CLC Number: