I find it a bit difficult to figure out how to use the precompile system properly. Documentation appears to be sparse.
A few months ago @tim.holy made an interesting post on my Github page:
He indicated that Julia will not generate machine code with the following unless I explicitly include the
precompile(bar, (Float64,)) statement:
__precompile__() module CC bar(x::Float64) = 2x precompile(bar, (Float64,)) end
I was surprised, because I assumed Julia would always precompile functions down to machine code when all arguments were concrete. However, I was able to confirm his statement: Indeed
mul_float only appeared in
CC.ji if I explicitly called
My experience with SnoopCompile.jl
I find it a bit difficult to use correctly - mostly because I don’t really understand how the precompile system works. It also seems like more complex packages require a fair amount of manual intervention for things to work smoothly.
So I thought of the following:
What if, instead, you defined a function that exercised the code you wish to pre-compile directly in your module?
That way, you could trigger the compilation of lower-level functions without having to explicitly add an entry for each one:
__precompile__() module CC bar(x::Float64) = 2x function precompile_sequence() #Trigger compilation of lower-level functions by exercising high level functions: bar(2.0) #A simple test #Add some high-level functions that exercise the user code here. #Maybe execute some of the built-in tests? return nothing end precompile(precompile_sequence, ()) end
This way, I don’t have to generate entries for each function I wish to precompile… as long as I can trigger a chain of calls that does this for me. I guess this is sort of how SnoopCompile.jl works… but without going through intermediate files, etc.
Would this work? Does anybody see issues with this methodology? It can be somewhat difficult to tell if I am using the precompile system correctly.