Abstract
Multi-stream SSDs can isolate data with different life time to disparate erase blocks, thus reduce garbage collection overhead and improve overall SSD performance. Applications are responsible for management of these device-level steams such as stream open/close and data-to-stream mapping. This requires application changes, and the engineer deploying the solution needs to be able to individually identify the streams in their workload. Furthermore, when multiple applications are involved, such as in VM or containerized environments, stream management becomes more complex due to the limited number of streams a device can support, for example, allocating streams to applications or sharing streams across applications will cause additional overhead. To address these issues and reduce the overhead of stream management, this paper proposes automatic stream management algorithms that operate under the application layer. Our stream assignment techniques, called AutoStream, is based on run time workload detection and independent of the application(s). We implement our AutoStream prototype in NVMe Linux device driver and our performance evaluation shows up to 60% reduction on WAF(Write Amplification Factor) and up to 237% improvement on performance compared to a conventional SSD device.
Published Version
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