Recently I've seen articles trying to sow FUD (fear, uncertainty, and doubt) where BeeGFS and other parallel file systems fit for machine learning and deep learning workloads, so I thought I'd do my part to help set the record straight. This post is an attempt to summarize all the "that's not quite right" moments I've had when reading what others have to say about BeeGFS online. If you're not familiar with BeeGFS, it’s a radically simple-to-use parallel file system (PFS) that can scale from the smallest artificial intelligence proof of concept to meet the most demanding super-sized production requirements.
Joe McCormick is a software engineer at NetApp with over ten years of experience in the IT industry. With nearly seven years at NetApp, Joe's current focus is developing high-performance computing solutions around E-Series. Joe is also a big proponent of automation, believing if you've done it once, why are you doing it again.