I was asked (on x.com) to dump some of my reading from the last two days on optimizing compilers – here they are. For context, I never actually wrote a compiler backend (I’m an LLVM baby), so while I’m specifically interested in optimizing compilers because of their allure. I have no hands-on tangible experiences with writing one.
What Every C Programmer Should Know About Undefined Behavior
Re-read the full wonderful series from Chris Lattner, to refresh my mind on UB. Give this one a read if you haven’t!
Future Directions for Optimizing Compilers
This served as a nice (if indirect) modern primer on optimizing compilers. Their main case studies were: Declarative Peephole Optimizations for LLVM, Superoptimizing LLVM
The references led me to:
instcombine
: Combine redundant instructions from LLVM -Google’s Souper: A superoptimizer for LLVM IR- googling about automated theorem provers, formal semantics…
It also made me realize I needed a refresher (or to actually learn) what SSA actually was. If you’re interested in optimizing compilers, these are some of the nicest, shorter resources I found on SSA:
- Understanding static single assignment forms -> by far the most concise resource I found, explaining SSA in LLVM’s world.
- Generating Better Machine Code with SSA -> this one was great too, from the POV of the Go compiler. Lots of nice illustrations for my grug brain.
- Diving Into Static Single Assignment With the Go Compiler -> another one from a Go compiler contributor that was high-quality.
- Introduction to the Go compiler’s SSA backend -> the two links above led me to take a peek at Go’s official doc on their SSA backend
- Static Single-Assignment Form Seminar -> found this random seminar from 2009 with tons of slides from different talk, helped fuel my thoughts with examples and parsing through some more information.
- SSA is Functional Programming -> random, fun 3-page read – apparently I have something in common with SSA people: we both love flowcharts
- Static Single Assignment Book -> this seems like a 300 page banger on SSA, saved for later (eg a degenerate sleepless night or a rainy day with no internet)
Learning to Make Compiler Optimizations More Effective
Very interesting read on a RNN-based model and pipeline for loop optimizations. It got me thinking about where/how do these ML-based techniques fit in existing or new compiler pipelines – held off on researching the current SOTA for this.
Some interesting quotes: > Given the source code of a loop, LoopLearner suggests a semantically invariant transformation that will likely allow the compiler to produce more efficient code.
Following its recommendations prior to compilation results in an average speedup of 1.14x. Almost three quarters (73%) of the suggested transformations yield positive speedups. Trying the top-3 recommendations and choosing the best one raises the average speedup even to 1.29x.
(to be used) as a pre-processor run before or as part of the compiler
What every compiler writer should know about programmers or “Optimization” based on undefined behaviour hurts performance
Tbh, the entire paper is a banger with lots of interesting takes (2.1, 3 especially go hard). It’s also a really funny read. Below are some quotes I thought were interesting.
This one stood out and captures C very well to me >Some of the facets of the spirit of C can be summarized in phrases like: – Trust the programmer. – Don’t prevent the programmer from doing what needs to be done. – Keep the language small and simple. – Provide only one way to do an operation. – Make it fast, even if it is not guaranteed to be portable. The last proverb needs a little explanation. The potential for efficient code generation is one of the most important strengths of C. To help ensure that no code explosion occurs for what appears to be a very simple operation, many operations are defined to be how the target machine’s hardware does it23 rather than by a general abstract rule.
Bold take on UB-based heuristics and its consequences > “Optimizations” based on assuming that undefined behavior does not happen buy little performance even for SPECint benchmarks (1.7% speedup with Clang3.1, 1.1% with GCC-4.7), and incur large costs: Most production programs perform undefined behaviors and removing them all requires a lot of effort, and may cause worse code to be produced for the program. Moreover, a number of security checks have been “optimized” away, leaving the affected programs vulnerable!

“[…] programs that work on a version of your compiler are conforming C programs and they are not buggy just because they perform undefined behavior”
Here’s one more (but really, the paper is full of these) I posted on x.com here.
Reading this I also realized I needeed a refresh on GCC optimization flags and went through a few rabbit holes using GCC’s 3.11 Options That Control Optimization
Stashed for later
Stashed for later can mean a lot of things. If it is directly relevant to my goals, that usually means tomorrow/once I’m rested. If it isn’t, it could be anytime from “next time I’m reading on that domain” to “in 9 months when I’m attempting to write an optimizing compiler”
- Taming Undefined Behavior in LLVM
- Towards Optimization-Safe Systems: Analyzing the Impact of Undefined Behavior
- THE DESIGN OF AN OPTIMIZING COMPILER (1973)
- GopherCon 2017: Keith Randall - Generating Better Machine Code with SSA
- Safe, Efficient, and Portable Rotate in C/C++? -> both interesting and I loved the layout of the blog, so will loop back to this one for sure