Junghan Kim  Young Ik Eom

10.5626/JOK.2022.49.1.8

Non-volatile memory persistent memory data structure NUMA flat combining

Recently, advances in persistent memory and NUMA technologies have allowed for the provision of high performance and large storage space to the applications such as big data and machine learning. Such PM environments on multi-node systems require a change in the data structures, which are being used in each layer of the software stack. In terms of the research on PM data structures, however, it is a difficult problem to ensure high level of concurrency as well as non-volatility which is an important characteristics of NUMA and PM, respectively. In this paper, we propose an NRPM that extends the node replication, which is a representative of NUMA algorithms. NRPM outperforms hash algorithm by up to 5x by improving concurrency in the multi-node PM server using shared-log and flat combining methods. We confirmed the validity of NRPM through various performance analyses considering the characteristics of NUMA-PM.