Re:Arm Announces Cortex-R82: First 64-Bit Real Time Processor
by wtallis on Monday September 07, 2020 @11:45PM
(#24405031)
> You could build query-by-example indexes (for text, sound, images or videos) in the storage hardware with this kind of capability. That'd be pretty interesting.
I've seen demos of this kind of thing from companies like NGD Systems, who use Cortex A53s in addition to realtime cores in their SSD controller. Part of the selling point for offloading this from the CPU is that code running on the SSD controller has much faster access to the dataset and can query it more efficiently, unconstrained by the drive's host interface.
There are also more mundane use cases for ML inside a SSD as heuristics to predict data access patterns or media wearout trends, which can influence how the SSD chooses to store data and tackle error correction.
Sure, why not? The number of instructions needed to run inference on a given neural network is known so I don't see any real issues here.
(Training is of course a different matter)
> Is it just me or sounds the "ML" on these slides more like "we need to join the hype" than an actual use-case?
You could build query-by-example indexes (for text, sound, images or videos) in the storage hardware with this kind of capability. That'd be pretty interesting.
Imagine something like Isilon, but instead of allowing Hadoop analytics on the storage hardware it could do approximate nearest neighbour across images.
(This is actually a pretty good idea...)