Cache hit rate is probably the most immediately useful. Although given that this is for always-on profiling maybe this project isn't as geared towards optimizing kernels as I originally thought? In theory reading the counters should be low overhead though.
[ All from my experience on home GPUs, and in lah with 2 nodes with 2 80GB H100 each. Not extensively benchmarked ]
Events like kernel launch, which this profiler reads right now, is a very small overhead (1-2%). Kernel level metrics like DRAM utilisation, cache hit rate, SM occupancy, etc usually give you a 5-10% overhead. If you want to plot a flame graph at a instruction level (mostly useful for learning purposes) then you go off the rails - even 25% overhead I have seen. And finally full traces add tons of overhead but that's pretty much expected - they anyways produce GBs of profiling data.
Occupancy and RAM utilization are available from static analysis. A sampling profiler would also obviously not be suitable for this always-on profiler case. But reading the counters [0] from the GSP should be cheap.
