3 ms·
A typical goal is 60hz, which is 17k microseconds. My cursory research says as of 10 years ago a typical write/receive latency for an nvidia card, i7, pcie2.0 i
by fnordpiglet 4y ago
A typical goal is 60hz, which is 17k microseconds. My cursory research says as of 10 years ago a typical write/receive latency for an nvidia card, i7, pcie2.0 is 20 microseconds. That gives you a large budget despite the fact SIMD on chip is measured in cycles not microseconds. Inside the GPU you have a huge amount of space and resources to do highly specialized operations in vast concurrency, I.e., bandwidth for compute is huge and specialized. I don’t see how CPU’s or SOC will solve this without vastly increasing die sizes and heat and power consumption to be close to that of a GPU with all its cooling requirements and heavy power needs.
That said I think the “good enough” metric is already there and unless you’re doing hardware ray tracing or extreme details at high resolutions you won’t need or care about a GPU any more.
Latency though isn’t the issue. The times involved for human perception are long and not getting shorter.
- fragmede 4y agoThings have been "good enough" since 2012. But then VSCode and bigger webpages came along and suddenly a Core2Duo just doesn't cut it anymore. ML models need somewhere to run, locally, and both Apple and Google have dedicated hardware on smartphones for that. Support for bigger and bigger models (read GPU performance) in smaller and smaller packages is just the latest iteration of progress.
- fnordpiglet 4y agoYes I agree. Except I think real time ray tracing really is that much better and shifts the goal posts again.