With enterprises increasing embracing HPC environments to help manage the tidal wave of data that’s washing over them and the rise of AI and machine learning workloads, tech vendors selling into the market need to demonstrate both flexibility and adaptability. …
In late 2018, HPC storage provider Panasas rolled out its re-engineered PanFS parallel file system based on Linux, a move designed to give the company and its technology a capability that has become key at a time when HPC-like workloads and emerging technologies like artificial intelligence (AI) and machine learning continue to spill beyond the confines of research institutions and government laboratories and into the enterprise: portability. …
Storage in the ever-expanding HPC space has traditionally been based on temperature. …
Storage systems are inherently data intensive. But the rapid emergence of artificial intelligence as a standard datacenter workload has storage vendors scrambling to design platforms that better meet the more stringent performance needs of these applications. …
After a decade of vendor consolidation that saw some of the world’s biggest IT firms acquire first-class HPC providers such as SGI, Cray, and Sun Microsystems, as well as smaller players like Penguin Computing, WhamCloud, Appro, and Isilon, it is natural to wonder who is next. …
Storage hierarchies just aren’t what they used to be.
In the good old days, you stored files on hard disk or magnetic tape. …
It used to be far easier to talk about storage performance, cost, and options. …
Storage is no longer an afterthought when it comes to systems of any reasonable scale. …
As we well know by now, workloads at supercomputing sites large and small are changing with the introduction of machine learning and more complex applications that require both large and small files. …
Changes to workloads in HPC mean alterations are needed up and down the stack—and that certainly includes storage. …
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