GPU-accelerated databases have a long history. I founded HeavyAI (previously MapD/OmniSci) in 2013, but there are or have been many other startups in this space, such as Voltron Data, Kinetica, Sqream, etc. And now you have major players like IBM, Starburst, and Microsoft (which just announced Fabric SQL on GPU today) working on their own GPU-accelerated systems. GPUs have a huge advantage in terms of compute, memory, and interconnect bandwidth over CPU, as long as you can keep them fed with data.
I believe within 2-3 years databases and data warehouses on GPU will be common. The widespread use of agents to query data will be a part of this, as there will be a need to run far more queries at lower latency than needed for the ETL and BI workloads of the past.
And smart NICs are moving significant amounts of compute directly onto the network interface, though I haven't seen anyone combining a GPU and a 100GbE NIC into a single part yet.
Where does a few more steps of evolution take us? A wide path between a few heavy devices, and then the CPU off to the side just orchestrating the data flow?
Insightful take, looking into these