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...this information to constraint the value range of v a bit more. My work is not part of the LLVM mainline yet. But I would be happy to contribute with the code of my range analysis implementation if it can help you in something else. Best, Douglas On Sun, Feb 20, 2011 at 2:30 PM, Gratian Lup <lgratian at gmail.com> wrote: > Hi! > I'm a student who would like to participate on Google SOC for LLVM, and was > thinking about what project to pick. I saw on the "Open projects" page that > Value Range Propagation is not implemented and thought about doing it, based > on...

Hi! I'm a student who would like to participate on Google SOC for LLVM, and was thinking about what project to pick. I saw on the "Open projects" page that Value Range Propagation is not implemented and thought about doing it, based on a paper by Patterson (it's also used by GCC). But then I saw that last year someone did a Range Analysis pass that seems to do pretty much the

Hi! I'm interested in profile-guided optimizations and was looking at the functionality LLVM provides. I have two questions: - can the current (optimal) edge profiling be used to determine the number of times a function calls another one? I need to know not only how many times a function was called, but also by whom. Or to say in in a different way, can a profile edge be formed from blocks

Hi! My name is Gratian and I would like to participate to GSOC 2011. I'm interested in profile-guided optimizations, and I want to implement two optimizations that can bring tangible benefits for most applications: profile-guided function inlining and basic block positioning. Inlining can be greatly improved if we take into consideration how many times the function we want to inline was

I recently downloaded LLVM 2.8 and started playing with the optimizations a bit. I saw something curious while trying the following function: int g(unsigned int a) { unsigned int c[100]; c[10] = a; c[11] = a; unsigned int b = c[10] + c[11]; if(b > a*2) a = 4; else a = 8; return a + 7; } The generated code, with -O3 activated, is define i32 @g(i32 a) nounwind readnone { %add = shl i32

1. Summary I will implement two optimizations in the LLVM compiler, both based on runtime profile information: an inlining mechanism that takes the call frequency into consideration, and a better basic block placement algorithm. 2. The project LLVM now includes an efficient framework [1] for instrumenting an application and collecting edge and path profile information. Profile-guided