In our use case, there is a Background Mac App (running on Mac M1) that is responsible for receiving data from a companion iOS App via WebSocket connection (client-side Apple Swift API, Vapor4 server side API) and perform computations using Metal Compute APIs and our custom kernels. In order to optimize execution time of these compute kernels we are looking for a way to profile their execution time i.e. how much combined GPU execution time (compute and memory accesses) is taken by each instance? As may be obvious, our primary focus is not the waiting time spent in the kernel scheduling queues before execution begins, but this may be helpful as an extra. We are not sure whether Instruments in XCode will be helpful in above scenario (partly in iOS, partly 3rd party WebSocket API, and partly background Mac App (command line App))? Also, is Metal frame capturing method dependent on presence of Metal graphics APIs and hence will not work for Background Apps? Can we get desired info using GPU Counter Sample Buffers, or are we looking at the wrong places? Any assistance wrt above (measurement of Metal compute kernel execution times in the context of a Mac Background App) will be highly appreciated.

As the description of XPC says that it can be used for inter process communication mechanism, what exactly the inter process means? Can it be used to create shared memory between any type of processes (ex. Swift Process (App) and any other language process) or it is for strictly App to App (swift to swift) communication?

For several reasons it is required to call the python functions from parallel threads, currently PythonKit library is being used for that. While one python module is running and if I try to execute the other module from other thread than it is giving EXC_BAD_ACCESS error. this error from internal code of PythonKit. Please guide me if I am missing something.

For some reasons it is required to send binary files from iOS app to MacOS Command line tool (CLT) app for the computation of data and also send back the computed results from maxOS CLT app to the iOS app. a) what is preferred way (using tools & framework from apple)? b) If it's not easy to achieve this using apple tools and frameworks; will "Vapor" be useful for this task?

To use some libraries which are easily available in python it is required to run the python files and get output from it from the MacOS app, What is the preferred way (from apple) to call python functions from swift?