Visible to the public Analysis and Mitigation of Data Sanitization Overhead in DAX File Systems

TitleAnalysis and Mitigation of Data Sanitization Overhead in DAX File Systems
Publication TypeConference Paper
Year of Publication2022
AuthorsPark, Soyoung, Kim, Jongseok, Lim, Younghoon, Seo, Euiseong
Conference Name2022 IEEE 40th International Conference on Computer Design (ICCD)
KeywordsBenchmark testing, composability, compositionality, data integrity, Data Sanitization, DAX, direct access, File systems, Low latency communication, persistent memory, pubcrawl, resilience, Resiliency, Resource management
AbstractA direct access (DAX) file system maximizes the benefit of persistent memory(PM)'s low latency through removing the page cache layer from the file system access paths. However, this paper reveals that data block allocation of the DAX file systems in common is significantly slower than that of conventional file systems because the DAX file systems require the zero-out operation for the newly allocated blocks to prevent the leakage of old data previously stored in the allocated data blocks. The retarded block allocation significantly affects the file write performance. In addition to this revelation, this paper proposes an off-critical-path data block sanitization scheme tailored for DAX file systems. The proposed scheme detaches the zero-out operation from the latency-critical I/O path and performs that of released data blocks in the background. The proposed scheme's design principle is universally applicable to most DAX file systems. For evaluation, we implemented our approach in Ext4-DAX and XFS-DAX. Our evaluation showed that the proposed scheme reduces the append write latency by 36.8%, and improved the performance of FileBench's fileserver workload by 30.4%, YCSB's workload A on RocksDB by 3.3%, and the Redis-benchmark by 7.4% on average, respectively.
NotesISSN: 2576-6996
DOI10.1109/ICCD56317.2022.00045
Citation Keypark_analysis_2022