VDURA has launched a preview of its V-ScaleFlow data movement tech in the latest rev of its Data Platform, which it claims will reduce flash requirements by over 50 percent.
The firm claimed V-ScaleFlow, part of its Data Platform v11.2 release, will allow “seamless data movement” across high-performance QLC flash and high-capacity disk.
This should, the firm claims, optimize utilization and maximize throughput in systems. More specifically, it will ensure GPUs are kept fully saturated.
VDURA flagged ScaleFlow as a possible fix for AI workflow bugbears such as the need for over-provisioned TLC flash or DRAM buffers to hadle write-intensive checkpoints.
Another proposed target problem is holding long-tailed datasets and artifacts in external object stores or tape, giving operators the option of using high density disk drives instead.
This could add up to a 50 percent reduction in flash capacity requirements it claimed, and lower power consumption overall.
Storage unsolved
When it comes to hyperscale or AI deployments, it can seem storage is a largely solved problem. It’s GPUs that grab most of the attention, followed by networks. But perhaps it’s more a case of storage is generally “good enough.”
A VDURA spokesperson said “Storage solutions typically struggle under the strain of billions of metadata operations, rapid checkpointing, and intensive I/O demands, leading to GPU idle times and diminished productivity. It’s critical to view the stages of the AI pipeline for performance, capacity, and cost efficiency when architecting infrastructure.”
He added: “Relying solely on all-flash solutions (focusing only on performance) across every stage leads to significant flash waste, inflated costs, and unnecessary power consumption.”
He claimed The Goethe University’s Center for Scientific Computing in Germany had overcome “critical storage bottlenecks” in its large-scale physics AI simulations and GPU-intensive tasks that had caused “severe disruptions and data losses” after adopting VDURA’s V5000 appliance.
Other new capabilities in 11.2 include end to end encryption and a Native CSI plug-in, which it said will simplify multi-tenant Kubernetes based deployments.
