Paper: Magellan: Autonomous Discovery of Novel Compiler Optimization Heuristics with AlphaEvolve

This Google paper describes an AI approach to invent new compiler
optimizations.


Abstract


Modern compilers rely on hand-crafted heuristics to guide optimization
passes. These human-designed rules often struggle to adapt to the
complexity of modern software and hardware and lead to high maintenance
burden. To address this challenge, we present Magellan, an agentic
framework that evolves the compiler pass itself by synthesizing executable
C++ decision logic. Magellan couples an LLM coding agent with evolutionary
search and autotuning in a closed loop of generation, evaluation on
user-provided macro-benchmarks, and refinement, producing compact
heuristics that integrate directly into existing compilers. Across several
production optimization tasks, Magellan discovers policies that match or
surpass expert baselines. In LLVM function inlining, Magellan synthesizes
new heuristics that outperform decades of manual engineering for both
binary-size reduction and end-to-end performance. In register allocation,
it learns a concise priority rule for live-range processing that matches
intricate human-designed policies on a large-scale workload. We also
report preliminary results on XLA problems, demonstrating portability
beyond LLVM with reduced engineering effort.


https://arxiv.org/abs/2601.21096


Regards,
John Levine, johnl@taugh.com, Taughannock Networks, Trumansburg NY
Please consider the environment before reading this e-mail. https://jl.ly

Return to the comp.compilers page.
Search the comp.compilers archives again.