I thought it was because the number logic elements in a GPU is orders of magnitude higher than in a FPGA, rather than just processing speed. And GPU processing is inherently parallel so the GPU beats the FPGA just based on transistor count.
With FPGA you are sacrificing performance for flexibility you are far less efficient in transistors for any given task than with a dedicated ASIC even if it’s a general compute ASIC like a GPU is today.
The reason no one is building large FPGAs is that there is no market for them.
If an H200 scale FPGA was viable we would have one.
dogma1138|5 days ago
The reason no one is building large FPGAs is that there is no market for them.
If an H200 scale FPGA was viable we would have one.