Analyzing parallelization performance of Reed-Solomon algorithm

Authors

  • Fabricio R. Marcillo University of Granada
  • Raúl H. Palacios Universidad Autónoma del Estado de Hidalgo
  • Antonio F. Díaz University of Granada
  • Jefferson R. Herrera Universidad de las Artes
  • Ronald D. Camacho Universidad Técnica Estatal de Quevedo

DOI:

https://doi.org/10.18779/ingenio.v4i1.365

Keywords:

Reliability, fault tolerance, error control codes, Reed-Solomon

Abstract

Distributed storage systems allow to solve the strong demand of data storage required by today's society, this is because new challenges arise related to data recovery based on erasure code. This article presents the parallelization of the Reed-Solomon algorithm through threads. The evaluation was made in a BLADE system, the execution of the algorithm has been done in a configuration of 1, 2, 4 and 8 threads to check the behavior of the algorithm. Regarding the results, it was observed that the times required for processing the algorithms for both encoding and decoding are considerably reduced.

Downloads

Download data is not yet available.

References

Palacios, R. H., Díaz, A. F., Anguita, M., Ortega, J., & Rodríguez-Quintana, C. (2017). High-throughput multi-multicast transfers in data center networks. The Journal of Supercomputing, 73(1), 152-163.

Palacios, R. H., Rodríguez-Quintana, C., Díaz, A. F., Anguita, M., & Ortega, J. (2017). Evaluation of redundant data storage in clusters based on multi-multicast and local storage. The Journal of Supercomputing, 73(1), 576-590.

Aguilera, M. K., Janakiraman, R., & Xu, L. (2005, June). Using erasure codes efficiently for storage in a distributed system. In 2005 International Conference on Dependable Systems and Networks (DSN'05) (pp. 336-345). IEEE.

Hafner, J. L. (2005, December). WEAVER Codes: Highly Fault Tolerant Erasure Codes for Storage Systems. In Fast (Vol. 5, pp. 16-16).

Khan, O., Burns, R. C., Plank, J. S., Pierce, W., & Huang, C. (2012, February). Rethinking erasure codes for cloud file systems: minimizing I/O for recovery and degraded reads. In FAST (p. 20).

Plank, J. S. (2013). Erasure codes for storage systems: A brief primer. ; login:: the magazine of USENIX & SAGE, 38(6), 44-50.

Weatherspoon, H., & Kubiatowicz, J. D. (2002, March). Erasure coding vs. replication: A quantitative comparison. In International Workshop on Peer-to-Peer Systems (pp. 328-337). Springer, Berlin, Heidelberg.

Rashmi, K. V., Shah, N. B., Ramchandran, K., & Kumar, P. V. (2017). Information-theoretically secure erasure codes for distributed storage. IEEE Transactions on Information Theory, 64(3), 1621-1646.

Yiu, M. M., Chan, H. H., & Lee, P. P. (2017, May). Erasure coding for small objects in in-memory kv storage. In Proceedings of the 10th ACM International Systems and Storage Conference (pp. 1-12).

Sobe, P. (2010, May). Parallel reed/solomon coding on multicore processors. In 2010 International Workshop on Storage Network Architecture and Parallel I/Os (pp. 71-80). IEEE.

Chen, R., & Xu, L. (2020). Practical performance evaluation of space optimal erasure codes for high-speed data storage systems. SN Computer Science, 1(1), 1-14.

Jin, H., Wu, C., Xie, X., Li, J., Guo, M., Lin, H., & Zhang, J. (2019, August). Approximate code: a cost-effective erasure coding framework for tiered video storage in cloud systems. In Proceedings of the 48th International Conference on Parallel Processing (pp. 1-10).

Plank, J. S., Simmerman, S., & Schuman, C. D. (2007). Jerasure: A library in C/C++ facilitating erasure coding for storage applications. Technical Report CS-07-603, University of Tennessee.

Published

2021-01-06

How to Cite

Marcillo, F. R., Palacios, R. H., Díaz, A. F., Herrera, J. R., & Camacho, R. D. (2021). Analyzing parallelization performance of Reed-Solomon algorithm. InGenio Journal, 4(1), 27–37. https://doi.org/10.18779/ingenio.v4i1.365

Issue

Section

Articles