From what I have read and benchmarks seen..
FPGA shines for writes (and up to 3x (as opposed to 10x claim) real world
for queries from memory)
GPU shines/outperforms FPGA for reads. There is a very recent and
interesting academic paper[1] on High Performance GPU B-Tree (vs lsm) and
the incredible performance it gets, but I 'think' it requires NVIDIA (so no
easy/super epyc+gpu+hbm on-chip combo solution then ;) ).
Doesn't both FPHGA and GPU going to require changes to executor from pull to
push to get real benefits from them? Isnt that something Andres working on
(pull to push)?
What really is exciting is UPMEM (little 500mhz processors on the memory),
cost will be little more than memory cost itself, and shows up to 20x
performance improvement on things like index search (from memory). C
library, claim only needs few hundred lines of code to integrate from
memory, but not clear to me what use cases it can also be used for than ones
they show benchmarks for.
[1] https://escholarship.org/content/qt1ph2x5td/qt1ph2x5td.pdf?t=pkvkdm
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