The performance of network file protocols is a critical factor in the efficiency of the AI and Machine Learning pipeline. This presentation provides a detailed comparative analysis of the two leading protocols, Server Message Block (SMB) and Network File System (NFS), specifically for demanding AI workloads.
We evaluate the advanced capabilities of both protocols, comparing SMB3 with SMB Direct and Multichannel against NFS with RDMA and multistream TCP configurations. The industry-standard MLPerf Storage benchmark is used to simulate realistic AI data access patterns, providing a robust foundation for our comparison. The core of this research focuses on quantifying the performance differences and identifying the operational and configuration overhead associated with each technology.
Compare Performance: Compare the performance of SMB (Direct, Multichannel) vs. NFS (RDMA, Multistream) under realistic AI workloads.
Evaluate Overhead: Evaluate the configuration complexity and operational overhead required for each storage protocol.
Select & Justify: Select the optimal protocol for a given AI task and justify the choice based on performance and complexity trade-offs.