People have been using GPU + DMA for low latency / real-time / high compute intensity applications for some time (using them for adaptive optics of all things).

People have been using GPU + DMA for low latency / real-time / high compute intensity applications for some time (using them for adaptive optics of all things). My PhD student's been cranking it to 100/200/400G, with 'just' DPDK, gpudev, and persistent cuda kernels.. Depends on the application, batching policy, compute intensity, etc. But you can put 8 NICs and 8 GPUs in one node (and have them communicate through nvlink, so huge intergpu bandwidth!) which I can't for CPUs. You can maybe also get some unobtainium A100X or CX7+H100 to skimp on PCIe if you're well funded...