Direct File Path Access with NVMe over Fabrics for High-Performance Remote Data Reads

Abstract

With AI workloads relying heavily on massive distributed datasets, the performance of remote file access has become crucial. Traditional remote file access mechanisms introduce significant overhead when retrieving data from storage, limiting performance in high-throughput applications. NVMe over Fabrics (NVMe-oF) is a remote file access mechanism designed for high-speed, low-latency access to remote block storage, making it a superior alternative to traditional solutions. However, NVMe is inherently a block-based protocol, meaning it does not natively support file names, directory structures, or POSIX semantics. In this paper, we design an approach to enable direct file-path reads over NVMe-oF, bridging the gap between high-performance block devices and file-oriented applications. Our approach streamlines data retrieval by leveraging NVMe’s high-speed architecture and low-latency capabilities, reducing unnecessary kernel interactions and optimizing I/O operations. Benchmark results show up to 2-14X improvement in remote read latency compared to existing approaches.