Selective On-Device Execution of Data-Dependent Read I/Os

Recent studies have demonstrated the benefits of employing on-device and in-kernel storage functions. On-device functions are primarily used to preprocess data within storage devices, effectively reducing the amount of I/O. In contrast, in-kernel functions are proposed to expedite sequences of data-dependent read I/O requests, particularly useful for applications traversing on-disk data structures. In this work, we investigate the unexplored potential of using on-device functions for data-dependent read I/O requests on read-only on-disk data structures. The results are promising: on-device I/O functions enable applications to issue I/O requests more rapidly and integrate seamlessly with in-kernel functions to efficiently manage high volumes of requests. We developed a prototype of this on-device function atop NVMeVirt, a stateof-the-art storage emulator. We demonstrate that on-device function enhances performance through experiments utilizing a simple B + -tree key-value store and WiredTiger, a widely used log-structured merge tree-based key-value store. Use of the on-device function improves the throughput of the B + -tree key-value store by up to 41%, and reduces WiredTiger's 99percentile tail latency on YCSB C by up to 3.85%, compared to the host-only in-kernel storage function.