We present PolyUFC, an MLIR based compilation flow for uncore frequency capping that combines (performance and power) roofline analyses and polyhedral compilation-based static analysis
for characterization of affine programs.
We introduce a parametric mathematical model that links operational intensity and uncore frequency to derive frequency caps, validated through empirical evaluation on real hardware.
By embedding these caps into Pluto optimized code generated by Polygeist, we achieve improvements in Energy Delay Product (EDP) up to $42%$ on compute-bound, and up to $54%$ on bandwidth-bound programs—carefully selected from ML-models from vision/NLP domains and PolyBench—over Intel UFS driver.
Our framework is retargetable across multiple micro-architectures; and can handle multiple optimization goals like performance, energy and EDP, and is applicable across inter/intra dialects.