Evolving a Retention Period Classifier for use with Flash Memory

Damien Hogan, Tom Arbuckle, Conor Ryan, Joe Sullivan

Abstract

Flash memory based Solid State Drives (SSDs) are gaining momentum toward replacing traditional Hard Disk Drives (HDDs) in computers and are now also generating commercial interest from enterprise data storage companies. However, storage locations in Flash memory devices degrade through repeated programming and erasing. As the storage blocks within a Flash device deteriorate through use, their ability to retain data while powered off over long periods also diminishes. Currently there is no way to predict whether a block will successfully retain data for a specified period of time while powered off. We detail our use of Genetic Programming (GP) to evolve a binary classifier which predicts whether blocks within a Flash memory device will still satisfactorily retain data after prolonged use, saving considerable amounts of testing time. This is the first time a solution to this problem has been proposed and results show an average of over 85% correct classification on previously unseen data.

References

  1. Aritome, S., Kirisawa, R., Endoh, T., Nakayama, R., Shirota, R., Sakui, K., Ohuchi, K., and Masuoka, F. (1990). Extended data retention characteristics after more than 10,000 write and erase cycles in EEPROMs. In International Reliability Physics Symposium. 28th Annual Proceedings., pages 259 -264.
  2. Aritome, S., Shirota, R., Hemink, G., Endoh, T., and Masuoka, F. (1993). Reliability issues of Flash memory cells. Proceedings of the IEEE, 81(5):776 -788.
  3. Brewer, J. and Gill, M. (2008). Nonvolatile Memory Technologies with Emphasis on Flash (A Comprehensive Guide to Understanding and Using Flash Memory Devices). Wiley-IEEE Press.
  4. Chen, F., Koufaty, D. A., and Zhang, X. (2009). Understanding intrinsic characteristics and system implications of Flash memory based solid state drives. In Proceedings of the Eleventh International Joint Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 7809, pages 181-192. ACM.
  5. Desnoyers, P. (2010). Empirical evaluation of NAND Flash memory performance. SIGOPS Oper. Syst. Rev., 44:50-54.
  6. Grupp, L. M., Caulfield, A. M., Coburn, J., Swanson, S., Yaakobi, E., Siegel, P. H., and Wolf, J. K. (2009). Characterizing Flash memory: Anomalies, observations, and applications. In Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 42, pages 24-33, New York, NY, USA. ACM.
  7. Kahng, D. and Sze, S. (1967). A floating-gate and its application to memory devices. The Bell System Technical Journal, 46(6):1288-1295.
  8. Koza, J. R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection. The MIT press.
  9. Luke, S. (2010). ECJ 20. A Java-based evolutionary computation research system. http://cs.gmu.edu/~eclab/projects/ecj/.
  10. Mielke, N., Belgal, H., Fazio, A., Meng, Q., and Righos, N. (2006). Recovery effects in the distributed cycling of Flash memories. In Reliability Physics Symposium Proceedings, 2006. 44th Annual., IEEE International, pages 29 -35.
  11. Mielke, N., Marquart, T., Wu, N., Kessenich, J., Belgal, H., Schares, E., Trivedi, F., Goodness, E., and Nevill, L. (2008). Bit error rate in NAND Flash memories. In Reliability Physics Symposium, 2008. IRPS 2008. IEEE International, pages 9-19.
  12. Pavan, P., Bez, R., Olivo, P., and Zanoni, E. (1997). Flash memory cells - an overview. Proceedings of the IEEE, 85(8):1248 -1271.
  13. Poli, R., Langdon, W. B., and McPhee, N. F. (2008). A Field Guide to Genetic Programming. Lulu.
  14. Shread, P. (2009). Fusion-io lowers the price of solid state storage. http://www.enterprisestorageforum.com/hardware/ news/article.php/3829246/Fusion-io-Lowers-thePrice -of-Solid-State-Storage.htm.
  15. Sullivan, J. and Ryan, C. (2011). A destructive evolutionary algorithm process. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 15:95-102. 10.1007/s00500-009-0513-2.
  16. Yaakobi, E., Ma, J., Grupp, L., Siegel, P., Swanson, S., and Wolf, J. (2010). Error characterization and coding schemes for Flash memories. In GLOBECOM Workshops (GC Wkshps), 2010 IEEE, pages 1856 -1860.
Download


Paper Citation


in Harvard Style

Hogan D., Arbuckle T., Ryan C. and Sullivan J. (2012). Evolving a Retention Period Classifier for use with Flash Memory . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 24-33. DOI: 10.5220/0004116200240033


in Bibtex Style

@conference{ecta12,
author={Damien Hogan and Tom Arbuckle and Conor Ryan and Joe Sullivan},
title={Evolving a Retention Period Classifier for use with Flash Memory},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)},
year={2012},
pages={24-33},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004116200240033},
isbn={978-989-8565-33-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)
TI - Evolving a Retention Period Classifier for use with Flash Memory
SN - 978-989-8565-33-4
AU - Hogan D.
AU - Arbuckle T.
AU - Ryan C.
AU - Sullivan J.
PY - 2012
SP - 24
EP - 33
DO - 10.5220/0004116200240033