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qtar: Design and Implementation of an Optimized tar Command with FTL-level Remapping
Jeongseok Ryoo, Sangwook Shane Hahn, Jihong Kim
http://doi.org/10.5626/JOK.2018.45.1.9
Tar is a Linux command that combines several files into a single file. Combining multiple small files into large files increases the compression efficiency and data transfer speed. However, tar has a problem in that smaller target files, result in a lower performance. In this paper, we show that this performance degradation occurs when tar reads the data from the target files and propose qtar (quick tar) to solve this problem via flash-level remapping. When the size of an I/O request is less than 1 MB, the I/O performance decreases proportionally to the decrease in size of the I/O request. Since tar reads the data of files one by one, a smaller file size results in a lower performance. Therefore, the remapping technique is implemented in qtar to read data from the target files at the maximum I/O size regardless of the size of each file. Our evaluations show that the execution time with qtar is reduced by up to 3.4 times compared to that with tar.
Garbage Collection Synchronization Technique for Improving Tail Latency of Cloud Databases
Seungwook Han, Sangwook Shane Hahn, Jihong Kim
http://doi.org/10.5626/JOK.2017.44.8.767
In a distributed system environment, such as a cloud database, the tail latency needs to be kept short to ensure uniform quality of service. In this paper, through experiments on a Cassandra database, we show that long tail latency is caused by a lack of memory space because the database cannot receive any request until free space is reclaimed by writing the buffered data to the storage device. We observed that, since the performance of the storage device determines the amount of time required for writing the buffered data, the performance degradation of Solid State Drive (SSD) due to garbage collection results in a longer tail latency. We propose a garbage collection synchronization technique, called SyncGC, that simultaneously performs garbage collection in the java virtual machine and in the garbage collection in SSD concurrently, thus hiding garbage collection overheads in the SSD. Our evaluations on real SSDs show that SyncGC reduces the tail latency of 99.9th and, 99.99th-percentile by 31% and 36%, respectively.
AIOPro: A Fully-Integrated Storage I/O Profiler for Android Smartphones
Sangwook Shane Hahn, Inhyuk Yee, Donguk Ryu, Jihong Kim
Application response time is critical to end-user response time in Android smartphones. Due to the plentiful resources of recent smartphones, storage I/O response time becomes a major key factor in application response time. However, existing storage I/O trace tools for Android and Linux give limited information only for a specific I/O layer which makes it difficult to combine I/O information from different I/O layers, because not helpful for application developer and researchers. In this paper, we propose a novel storage I/O trace tool for Android, called AIOPro (Android I/O profiler). It traces storage I/O from application - Android platform - system call - virtual file system - native file system - page cache - block layer - SCSI layer and device driver. It then combines the storage I/O information from I/O layers by linking them with file information and physical address. Our evaluations of real smartphone usage scenarios and benchmarks show that AIOPro can track storage I/O information from all I/O layers without any data loss under 0.1% system overheads.
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