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Journal of Signal Processing Systems

, Volume 84, Issue 1, pp 151–162 | Cite as

Data Allocation with Minimum Cost under Guaranteed Probability for Multiple Types of Memories

  • Shouzhen Gu
  • Qingfeng Zhuge
  • Juan Yi
  • Jingtong Hu
  • Edwin H.-M. Sha
Article

Abstract

As the advance of memory technologies, multiple types of memories such as different kinds of non-volatile memory (NVM), SRAM, DRAM, etc. provide a flexible configuration considering performance, energy and cost. For improving the performance of systems with multiple types of memories, data allocation is one of the most important tasks. The previous studies on data allocation problem assume the worst (fixed) case of data-access frequencies. However, the data allocation produced by employing worst case usually leads to an inferior performance for most of time. In this paper, we model this problem by probabilities and design efficient algorithms that can give optimal-cost data allocation with a guaranteed probability. We propose DAGP algorithm produces a set of feasible data allocation solutions which generates the minimum access time or cost guaranteed by a given probability. We also propose a polynomial-time algorithm, MCS algorithm, to solve this problem. The experiments show that our technique can significantly reduce the access cost compared with the technique considering worst case scenario. For example, comparing with the optimal result generated by employing the worst cases, DAGP can reduce memory access cost by 9.92 % on average when guaranteed probability is set to be 0.9. Moreover, for 90 percents of cases, memory access time is reduced by 12.47 % on average. Comparing with greedy algorithm, DAGP and MCS can reduce memory access cost by 78.92 % and 44.69 % on average when guaranteed probability is set to be 0.9.

Keywords

Guaranteed probability Data allocation Minimum cost Multiple types of memories Non-volatile memory 

Notes

Acknowledgements

This work is partially supported by National 863 Program 2013AA013202, Chongqing High-Tech Research Program csct2012ggC40005, NSFC 61173014, NSFC 61472052.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Shouzhen Gu
    • 1
  • Qingfeng Zhuge
    • 1
    • 3
  • Juan Yi
    • 1
  • Jingtong Hu
    • 2
  • Edwin H.-M. Sha
    • 1
    • 3
  1. 1.College of Computer ScienceChongqing UniversityChongqingChina
  2. 2.School of Electrical and Computer EngineeringOklahoma State UniversityStillwaterUSA
  3. 3.Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of EducationChongqingChina

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