Omega: A Hardware-Software Framework for Complete Design Space Exploration of FPGA-Based Heterogeneous Multi-Core SoCs

The design space exploration (DSE) of heterogeneous multi-core systems-on-chip (SoCs) presents a massive challenge due to the vast and complex configuration space, demanding simultaneous optimization of performance, energy efficiency, and resource utilization under diverse constraints. Traditional approaches leveraging analytical models, heuristics, and machine learning (ML) techniques fail to comprehensively cover this space, often yielding suboptimal solutions. The Omega framework, designed for exhaustive DSE of FPGA-based heterogeneous multi-core SoCs, addresses the former limitations by fully exploring the design space and guaranteeing the identification of globally optimal configurations. Omega leverages FPGAs' dynamic partial reconfiguration to accelerate the DSE drastically and can serve as a golden model for evaluating novel DSE heuristics and ML methods. This manuscript demonstrates the proposed framework's effectiveness through an extensive experimental campaign on 16-core SoCs with accelerators for up to five different applications, achieving a substantial speedup, of 29 times on average, compared to traditional techniques while ensuring solution optimality. Omega is released as a comprehensive open-source ecosystem, compatible with commercially available FPGA platforms, to facilitate future research and practical adoption, setting a new benchmark for DSE methodologies and providing a robust tool for optimizing next-generation computing platforms.