Cross posting my answer in case someone comes across this discussion but not the other (Solving UDE segfaults or runs with poor performance - #6 by wsmoses).
Warning: Using fallback BLAS replacements, performance may be degraded
In essence, this says we have not finished implementing our internal BLAS and have a fallback implementation which exists and is correct, but is single core and may be substantially slower. Ironically we are presently on the verge of merging the much faster one for most cases of dot product, matrix multiply, and matrix vector multiply (Gemv by ZuseZ4 · Pull Request #1208 · EnzymeAD/Enzyme · GitHub) with more coming soon. cc @ZuseZ4 who is leading that effort (though FYI that branch doesn’t support runtime activity yet).
The BLAS isn’t a warning you can fix normally, but is an internal feature that is under development. That said you can work around it by writing a custom Enzyme rule (Custom rules · Enzyme.jl). Finding where to write it however, may be a bit more tricky without the better backtraces having landed in LLVM.jl.
Unfortunately the back traces at the moment are limited to basically a few function calls back until the corresponding PR’s to the latest Julia and LLVM.jl land to enable better backtraces (Add Interface to julia OJIT by gbaraldi · Pull Request #346 · maleadt/LLVM.jl · GitHub), (Expose the Julia JIT with a C API by gbaraldi · Pull Request #49858 · JuliaLang/julia · GitHub). I’m told this will only enable it for the (not released) Julia 1.10, but maybe if you ask nicely enough someone can be convinced to backport it.