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Towards AI-Augmented Co-Compilation for Smart IoT Systems Through Domain-Specific LLMs

Fulltext:


Authors:

Federico Ciccozzi

Research group:

Automated Software language and SOftware engineering

Publication Type:

Conference/Workshop Paper

Venue:

10th INTERNATIONAL CONFERENCE ON SMART AND SUSTAINABLE TECHNOLOGIES

Abstract

The explosion of smart, interconnected IoT devices is driving demand for higher performance, real‑time processing, and self‑* capabilities (self‑adaptation, self‑reconfiguration, self‑healing) across heterogeneous platforms. CPUs, GPUs, and FPGAs now provide exceptional compute power but greatly complicate software toolchains. We envision AI‑COMPILER, an LLM‑driven, domain‑specific framework that automates co‑compilation and optimization of heterogeneous applications in smart cities, smart transportation, and real‑time analytics. Tackling multi‑objective goals—power efficiency, reliability, and dynamic reconfiguration—AI‑COMPILER aims to transform how IoT and edge infrastructures are developed, deployed, and maintained. We examine critical issues such as generalization to new hardware, human‑AI collaborative tuning, and semantic coherence across multiple DSLs, arguing that AI‑COMPILER can usher in more agile, resilient IoT ecosystems through flexible, context‑aware code generation and adaptation.

Bibtex

@inproceedings{Ciccozzi7188,
author = {Federico Ciccozzi},
title = {Towards AI-Augmented Co-Compilation for Smart IoT Systems Through Domain-Specific LLMs},
month = {July},
year = {2025},
booktitle = {10th INTERNATIONAL CONFERENCE ON SMART AND SUSTAINABLE TECHNOLOGIES},
url = {http://www.es.mdu.se/publications/7188-}
}