You might be underestimating the intricacy of the CPU models LLVM uses. If you want to see them in action, the same data drives llvm-mca[1], which given a loop

You might be underestimating the intricacy of the CPU models LLVM uses. If you want to see them in action, the same data drives llvm-mca[1], which given a loop body can tell you the throughput, latency, and microarchitectural bottlenecks (decoding, ports, dependencies, store forwarding, etc.)—if not always precisely, then still as well on average as, say, x86’s IACA, the tool written at Intel by people who presumably knew how those CPUs work, unlike LLVM contributors and the rest of us who can only guess and measure. This separately for Haswell, Sandy Bridge, Skylake, etc.; not “x86”. Now, is this the best model you can get? Not exactly[2], but it’s close enough to not matter. Do we often need machine code optimized that finely? Perhaps not[3], and if you’re using generic distro binaries, you’re not getting it, either. (Unlike Facebook, Google, etc., who know precisely what their servers have inside, and who fund or contribute sizable portions of this optimization work.) With that in mind you can shave at least a factor of ten off LLVM’s considerable bulk at the cost of 20—30% of performance[4,5]. But if you do want those as well, it seems that the complexity of LLVM is a fair price, or has the right order of magnitude at least. (Frontend not included, C++ frontend required to bootstrap sold separately, at a similar markup compared to a C-only frontend with somewhat worse ergonomics.) [1] https://llvm.org/docs/CommandGuide/llvm-mca.html https://llvm.org/docs/CommandGuide/llvm-mca.html [2] https://www.uops.info/ https://www.uops.info/ [3] https://briancallahan.net/blog/20211010.html https://briancallahan.net/blog/20211010.html [4] https://c9x.me/compile/ https://c9x.me/compile/ [5] https://drewdevault.com/talks/qbe.html https://drewdevault.com/talks/qbe.html