Cerasure: Fast Acceleration Strategies For XOR-Based Erasure Codes

Erasure coding is a common redundancy scheme for tolerating failures in storage systems. Compared with replication, erasure coding saves a large amount of storage space, but incurs heavy computation overhead and thus is more time-consuming. To this end, we design an algorithm to find a better parity coding matrix to reduce the number of XORs in coding based on Vandermonde matrices instead of Cauchy matrices. In addition, we optimize the coding process, to accelerate the computation speed of XOR and obtain a better tradeoff between spatial locality and computation efficiency. For wide stripes which becomes increasingly interesting, we propose to decompose the coding procedure into multiple subprocedures for better utilization of spatial locality. We integrate these methods into coding procedure and implement an erasure coding library, Cerasure. Extensive experiments show that Cerasure significantly improves the coding speed. Compared with the state-of-the-art erasure coding libraries, Zerasure and SLPEC, Cerasure increases the encoding throughput by up to 109.47%.