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Design of Durable Node Replication for Persistent Memory Data Structures on NUMA Architectures
http://doi.org/10.5626/JOK.2022.49.1.8
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.
Distributed Storage System for Reducing Write Amplification on Non-Volatile Memory
http://doi.org/10.5626/JOK.2020.47.2.129
Recently, research on non-volatile memory, such as 3DXpoint, in distributed storage systems has received considerable interest from both academia and industry. However, in order to utilize these state-of-the-art non-volatile memory devices effectively in distributed storage systems, there is a need for improvements in traditional architectures of HDD/SSD-based storage systems. This is because current distributed storage system structures use a dedicated space for journaling to make up for slow storage performance. Also, considering the performance characteristics of non-volatile memory, which are similar to that of DRAM, current distributed storage system structures are not only inefficient in terms of overall performance but also cause write amplification. In this paper, we propose an architecture that mitigates the effects of write amplification in non-volatile memory-based distributed storage systems. To evaluate the proposed architecture and scheme, we have conducted diverse experiments in a CEPH storage system environment. Through these experiments, we have confirmed that the DAXNJ structure proposed in this paper decreases write amplification by 61% during 1M object write operations and increases the overall system performance by 15%.
An NVM-based Efficient Write-Reduction Scheme for Block Device Driver Performance Improvement
http://doi.org/10.5626/JOK.2019.46.10.981
Recently, non-volatile memory (NVRAM) has attracted substantial attention as a next-generation storage device due to the fact that it shows higher read/write performance than flash-based storage as well as higher cost-effectiveness than DRAM. One way to use NVRAM as a storage device is to modify the existing file system layer or block device layer. Leveraging the NVRAM block device driver is advantageous in terms of overall system compatibility, as it does not require any modification of the existing storage stack. However, when considering the byte-level addressing of the NVRAM device, the block write is not effective in terms of durability or performance. In this paper, we propose a block device driver that attempts to optimize the existing block write operations while considering the existing functionalities of the file system. The proposed block write reduction scheme provides a partial block write by classifying the type of blocks according to the structure of the file system as well as the amount of data modified in the block using XOR operation. Several experiments are performed to validate the performance of the proposed block device driver under various workloads, and the results show that, compared to the conventional block write operations, the amount of writes is reduced by up to 90%.
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