yogishbaliga

It is also other features such as GitHub workflow, releases, integration with other tools, webhooks etc. that makes it useful.

If it is unified memory, CPU can access the result of GPU processing without copying it to CPU memory (theoretically)

Way back in time, I used delta encoding for storing posting list (inverted index for search index). I experimented with using GPUs for decoding the posting list. It turned out that, as another reply mentioned copying posting list from CPU memory to GPU memory was taking way too long. If posting list is static, it can be copied to GPU memory once. This will make the decoding faster. But still there is a bottle neck of copying the result back into CPU memory.

Nvidia's unified memory architecture may make it better as same memory can be shared between CPU and GPU.

Very true, but in recent years feature development has taken precedence over efficiency. VP of whatever says hardware is cheap, software engineers are not.