A Cost-Effective Distribution-Aware Data Replication Scheme for Parallel I/O Systems

As data volumes of high-performance computing applications continuously increase, low I/O performance becomes a fatal bottleneck of these data-intensive applications. Data replication is a promising approach to improve parallel I/O performance. However, most existing strategies are designed based on the assumption that contiguous requests are being served more efficiently than non-contiguous requests, which is not necessarily true in a parallel I/O system. The reason is that the multiple-server data distribution makes the favorable accesses between contiguous requests and non-contiguous ones indeterminate. In this study, we propose CEDA, a cost-effective distribution-aware data replication scheme to better support parallel I/O systems. As logical file access information is inefficient to make replication decisions in a parallel environment, CEDA considers physical data accesses on servers in both data selection and data placement during a parallel replication process. Specifically, CEDA first proposes a distribution-aware cost model to evaluate the file request time with a given data layout, and then it carries out cost-effective data replication based on replication benefit analysis. We have implemented CEDA as a part of the MPI I/O library in light of high portability on top of the OrangeFS file system. By replaying representative benchmarks and a real application, we collected comprehensive experimental results on both HDD- and SSD-based servers and conclude that CEDA can significantly improve parallel I/O system performance.