I don't think you quite understand the problem. The problem wasn't turning on optimizations or getting debug info, the problem was getting Eigen-based linear al

I don't think you quite understand the problem. The problem wasn't turning on optimizations or getting debug info, the problem was getting Eigen-based linear algebra code to run at a sufficiently reasonable speed when optimizations were disabled because doing so would make other surrounding logic easier to debug (or you needed to run some analysis tool like Valgrind on a debug build). For example, we had simulation test suites which would run ~30 seconds of real-world time. If we can run those sims at 10x real time, each only takes 3 seconds, great! But with optimizations turned off, heavy Eigen code would run 1000x slower, which means the sims now take nearly 3000 seconds to run when bug hunting in the non-Eigen related surrounding logic. This already makes the test suite virtually un-runnable in debug builds, but if you want to then run those binaries through Valgrind (which tacks on another 100-1000x performance tax) you're now talking about something which is completely intractable. You can't run optimized builds through Valgrind without potentially introducing false positives, so you can't even run Valgrind on only the optimized builds... you just can't run it at all because your linear algebra library is slowing everything down. The core problem is Eigen's heavy use of expression templates, which the optimizer cuts through just fine. But without the optimizer turned on, it adds layers and layers and layers of unnecessary abstraction. Because these are all templates, C++ expands all this code at every call site, making it substantially less efficient and impossible to shim out by linking with an optimized build of Eigen itself. The only approach I've seen get close to making this work was an attempt by an engineer to use explicit template instantiation to create a separate binary with all the necessary Eigen functions which could be compiled separately with the optimizer turned on. However, this proved too nightmarish because since Eigen can template on the dimensions of everything, you need to know up front exactly all the various instantiations of Eigen types the program uses. This might be doable by writing a clang plugin or something, but doing it by hand was just way too much work because the codebase was huge, so we couldn't justify spending more time on it.