Themis: Malicious Wear Detection and Defense for Persistent Memory File Systems

2020 ◽  
Author(s):  
Wenbin Wang ◽  
Chaoshu Yang ◽  
Runyu Zhang ◽  
Shun Nie ◽  
Xianzhang Chen ◽  
...  
Keyword(s):  
File Systems ◽  
Persistent Memory

Octopus + : An RDMA-Enabled Distributed Persistent Memory File System

2021 ◽  
Vol 17 (3) ◽  
pp. 1-25
Author(s):  
Bohong Zhu ◽  
Youmin Chen ◽  
Qing Wang ◽  
Youyou Lu ◽  
Jiwu Shu
Keyword(s):  
High Speed ◽  
High Performance ◽  
File System ◽  
Direct Memory Access ◽  
File Systems ◽  
Distributed File Systems ◽  
Persistent Memory ◽  
Memory Modules ◽  
Non Volatile Memory ◽  
Volatile Memory

Non-volatile memory and remote direct memory access (RDMA) provide extremely high performance in storage and network hardware. However, existing distributed file systems strictly isolate file system and network layers, and the heavy layered software designs leave high-speed hardware under-exploited. In this article, we propose an RDMA-enabled distributed persistent memory file system, Octopus + , to redesign file system internal mechanisms by closely coupling non-volatile memory and RDMA features. For data operations, Octopus + directly accesses a shared persistent memory pool to reduce memory copying overhead, and actively fetches and pushes data all in clients to rebalance the load between the server and network. For metadata operations, Octopus + introduces self-identified remote procedure calls for immediate notification between file systems and networking, and an efficient distributed transaction mechanism for consistency. Octopus + is enabled with replication feature to provide better availability. Evaluations on Intel Optane DC Persistent Memory Modules show that Octopus + achieves nearly the raw bandwidth for large I/Os and orders of magnitude better performance than existing distributed file systems.

Efficient Multi-Grained Wear Leveling for Inodes of Persistent Memory File Systems

2020 ◽  
Author(s):  
Chaoshu Yang ◽  
Duo Liu ◽  
Runyu Zhang ◽  
Xianzhang Chen ◽  
Shun Nie ◽  
...  
Keyword(s):  
File Systems ◽  
Wear Leveling ◽  
Persistent Memory

Optimizing synchronization mechanism for block-based file systems using persistent memory

2020 ◽  
Vol 111 ◽  
pp. 288-299
Author(s):  
Chaoshu Yang ◽  
Qingfeng Zhuge ◽  
Xianzhang Chen ◽  
Edwin H.-M. Sha ◽  
Duo Liu ◽  
...  
Keyword(s):  
File Systems ◽  
Synchronization Mechanism ◽  
Persistent Memory ◽  
Block Based

scholarly journals An Empirical Evaluation of NVM-Aware File Systems on Intel Optane DC Persistent Memory Modules

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1977
Author(s):  
Guangyu Zhu ◽  
Jaehyun Han ◽  
Sangjin Lee ◽  
Yongseok Son
Keyword(s):  
Data Management ◽  
Empirical Evaluation ◽  
File Systems ◽  
Data Management System ◽  
Nand Flash ◽  
Storage Devices ◽  
Persistent Memory ◽  
Memory Modules ◽  
And Performance ◽  
And Storage

The emergence of non-volatile memories (NVM) brings new opportunities and challenges to data management system design. As an important part of the data management systems, several new file systems are developed to take advantage of the characteristics of NVM. However, these NVM-aware file systems are usually designed and evaluated based on simulations or emulations. In order to explore the performance and characteristics of these file systems on real hardware, in this article, we provide an empirical evaluation of NVM-aware file systems on the first commercially available byte-addressable NVM (i.e., the Intel Optane DC Persistent Memory Module (DCPMM)). First, to compare the performance difference between traditional file systems and NVM-aware file systems, we evaluate the performance of Ext4, XFS, F2FS, Ext4-DAX, XFS-DAX, and NOVA file systems on DCPMMs. To compare DCPMMs with other secondary storage devices, we also conduct the same evaluations on Optane SSDs and NAND-flash SSDs. Second, we observe how remote NUMA node access and device mapper striping affect the performance of DCPMMs. Finally, we evaluate the performance of the database (i.e., MySQL) on DCPMMs with Ext4 and Ext4-DAX file systems. We summarize several observations from the evaluation results and performance analysis. We anticipate that these observations will provide implications for various memory and storage systems.

Contour: A Process Variation Aware Wear-Leveling Mechanism for Inodes of Persistent Memory File Systems

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Xianzhang Chen ◽  
Edwin H.-M. Sha ◽  
Xinxin Wang ◽  
Chaoshu Yang ◽  
Weiwen Jiang ◽  
...  
Keyword(s):  
Process Variation ◽  
File Systems ◽  
Wear Leveling ◽  
Persistent Memory

scholarly journals InK: In-Kernel Key-Value Storage with Persistent Memory

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1913
Author(s):  
Minjong Ha ◽  
Sang-Hoon Kim
Keyword(s):  
High Performance ◽  
File Systems ◽  
Cloud Service ◽  
Main Memory ◽  
Storage Device ◽  
Storage Devices ◽  
Persistent Memory ◽  
Non Volatile Memory ◽  
Long Time ◽  
Block Based

Block-based storage devices exhibit different characteristics from main memory, and applications and systems have been optimized for a long time considering the characteristics in mind. However, emerging non-volatile memory technologies are about to change the situation. Persistent Memory (PM) provides a huge, persistent, and byte-addressable address space to the system, thereby enabling new opportunities for systems software. However, existing applications are usually apt to indirectly utilize PM as a storage device on top of file systems. This makes applications and file systems perform unnecessary operations and amplify I/O traffic, thereby under-utilizing the high performance of PM. In this paper, we make the case for an in-Kernel key-value storage service optimized for PM, called InK. While providing the persistence of data at a high performance, InK considers the characteristics of PM to guarantee the crash consistency. To this end, InK indexes key-value pairs with B+ tree, which is more efficient on PM. We implemented InK based on the Linux kernel and evaluated its performance with Yahoo Cloud Service Benchmark (YCSB) and RocksDB. Evaluation results confirms that InK has advantages over LSM-tree-based key-value store systems in terms of throughput and tail latency.

Sign in / Sign up

Export Citation Format

Share Document