# Hardware Counted Profile-Guided Optimization

arXiv: https://arxiv.org/abs/1411.6361 · HTML: https://mlsanity.com/paper/1411.6361/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Nov 2014.

## Built on by (most cited first, 2 of 2)

- [AI-PROPELLER: Warehouse-Scale Interprocedural Code Layout Optimization with AlphaEvolve](https://mlsanity.com/paper/2606.00131/) (2026)
- [AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning](https://mlsanity.com/paper/2606.20373/) (2026)

## Abstract (arXiv)

Profile-Guided Optimization (PGO) is an excellent means to improve the performance of a compiled program. Indeed, the execution path data it provides helps the compiler to generate better code and better cacheline packing. At the time of this writing, compilers only support instrumentation-based PGO. This proved effective for optimizing programs. However, few projects use it, due to its complicated dual-compilation model and its high overhead. Our solution of sampling Hardware Performance Counters overcome these drawbacks. In this paper, we propose a PGO solution for GCC by sampling Last Branch Record (LBR) events and using debug symbols to recreate source locations of binary instructions. By using LBR-Sampling, the generated profiles are very accurate. This solution achieved an average of 83% of the gains obtained with instrumentation-based PGO and 93% on C++ benchmarks only. The profiling overhead is only 1.06% on average whereas instrumentation incurs a 16% overhead on average.