TY - GEN
T1 - PPM
T2 - 44th International Conference on Parallel Processing, ICPP 2015
AU - Li, Shiyi
AU - Cao, Qiang
AU - Wan, Shenggang
AU - Zhang, Wenhui
AU - Xie, Changsheng
AU - He, Xubin
AU - Subedi, Pradeep
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/8
Y1 - 2015/12/8
N2 - Erasure codes are widely deployed in storage systems and the encoding/decoding process is a common operation in erasure-coded systems. Parity-check matrix method is a general method employed in erasure codes to conduct encoding/decoding process. However, the process is serial and generates high computational cost in dealing with matrix operations, and hence, causes low encoding/decoding performance. Especially for some recently proposed erasure codes, including SD code, PMDS code, and LRC code, the disadvantages are more obvious. To address this issue, in this paper, we present an optimization algorithm, called Partitioned and Parallel Matrix (PPM) algorithm, to accelerate the encoding/decoding processes of these codes by partitioning the parity-check matrix, parallelizing the encoding/decoding operations, and optimizing the calculation sequence, so as to achieve the goal of fast encoding/decoding. Experimental results show that PPM can speed up the encoding/decoding process of these codes by up to 210.81%.
AB - Erasure codes are widely deployed in storage systems and the encoding/decoding process is a common operation in erasure-coded systems. Parity-check matrix method is a general method employed in erasure codes to conduct encoding/decoding process. However, the process is serial and generates high computational cost in dealing with matrix operations, and hence, causes low encoding/decoding performance. Especially for some recently proposed erasure codes, including SD code, PMDS code, and LRC code, the disadvantages are more obvious. To address this issue, in this paper, we present an optimization algorithm, called Partitioned and Parallel Matrix (PPM) algorithm, to accelerate the encoding/decoding processes of these codes by partitioning the parity-check matrix, parallelizing the encoding/decoding operations, and optimizing the calculation sequence, so as to achieve the goal of fast encoding/decoding. Experimental results show that PPM can speed up the encoding/decoding process of these codes by up to 210.81%.
KW - Computational cost
KW - Erasure Codes
KW - Fault Tolerance
KW - Optimization Algorithm
KW - Parallelism
KW - Storage system
UR - https://www.scopus.com/pages/publications/84976465966
U2 - 10.1109/ICPP.2015.55
DO - 10.1109/ICPP.2015.55
M3 - 会议稿件
AN - SCOPUS:84976465966
T3 - Proceedings of the International Conference on Parallel Processing
SP - 460
EP - 469
BT - Proceedings - 2015 44th International Annual Conference on Parallel Processing, ICPP 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 September 2015 through 4 September 2015
ER -