Typical NAND chips present in SSDs have steadily evolved in speed and capacity over time, with contemporary server-grade units capable of reaching 28 GB/s per unit . Somehow, that's still not enough for the AI world. In turn, SK Hynix and SanDisk have jointly announced HBF , or High Bandwidth Flash, for the inference servers of tomorrow.
Power efficiency is apparently a concern for the standard-bearers, a pretty understandable notion in this day and age, where datacenters have massive wattage needs. A high-end Micron 9650 SSD pulls 25 W at full tilt, a figure that gets really ugly really fast when you think in exabyte-scale deployments with tens of thousands of drives.
There are no specifics on how this new HBF is meant to interact with systems, but the vague wording of "supporting layer" could mean it would be analogous to an on-SSD cache, but much bigger. It could also be a really fast block storage device a la Optane that applications and/or operating systems would have to be tweaked to use efficiently.
The announcement offers no target date, but it mentions that "demand of complex memory solutions, including HBF, will pick up around 2030", so that's as a good estimate as any for a production release date. The standard will be under the purview of the Open Compute Project . The companies are targeting HBF at inference servers, given that the outputs that bots users produce needs to be stored somewhere, and that storage need is projected to grow exponentially.
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