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Genetic optimisation of C++ applications
2021·IEEE/ACM ASE 2021
Figure 1: Container choice as a search space. Interchangeable data structures are swapped under genetic search (a); compiled variants are measured, and the dominated ones discarded (b).∎
C++ programs commit to containers early and revisit them never. This work automates the exploration: genetic search over interchangeable data-structure choices and their parameters, with each variant compiled, run, and measured on real workloads.
Across tested C++ libraries the search found notable reductions in CPU usage, runtime, and memory — headroom that had survived expert review precisely because no human systematically searches a space this large.
Key results
- Notable CPU, runtime, and memory reductions on real C++ libraries
- Fully automated explore–transform–measure loop
- Published at IEEE/ACM ASE 2021