Tools and Methodologies for System-Level Design

2025-07-13

AI Summary

To address critical challenges in SoC design—including ambiguous system-level modeling semantics, poor interoperability across heterogeneous computational models (e.g., dataflow and neural networks), and the decoupling of design-space exploration from verification—this paper proposes a co-communication mechanism ensuring semantic consistency across multiple models. The approach establishes an integrated toolchain supporting system-level modeling, simulation-driven verification, hardware-software co-design space exploration, and joint power-performance analysis. Innovatively, it unifies dataflow modeling with system-level abstractions to enable functional correctness verification and quantitative energy-efficiency evaluation for representative applications such as video processing and AI acceleration. Experimental results demonstrate that the methodology significantly improves early-stage SoC design iteration efficiency and enhances the reliability of architectural decision-making.

Technology Category

• Machine Learning: Hardware-aware ML
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

System-level design, once the province of board designers, has now become a central concern for chip designers. Because chip design is a less forgiving design medium -- design cycles are longer and mistakes are harder to correct -- system-on-chip designers need a more extensive tool suite than may be used by board designers and a variety of tools and methodologies have been developed for system-level design of systems-on-chips (SoCs). System-level design is less amenable to synthesis than are logic or physical design. As a result, system-level tools concentrate on modeling, simulation, design space exploration, and design verification. The goal of modeling is to correctly capture the system's operational semantics, which helps with both implementation and verification. The study of models of computation provides a framework for the description of digital systems. Not only do we need to understand a particular style of computation, such as dataflow, but we also need to understand how different models of computation can reliably communicate with each other. Design space exploration tools, such as hardware/software co-design, develop candidate designs to understand trade-offs. Simulation can be used not only to verify functional correctness but also to supply performance and power/energy information for design analysis. This chapter employs two applications -- video and neural networks -- as examples. Both are leading-edge applications that illustrate many important aspects of system-level design.

Problem

• Developing tools for system-level design of SoCs
• Modeling and verifying system operational semantics
• Exploring design trade-offs via simulation and co-design

Innovation

• System-level tools focus on modeling and simulation
• Design space exploration via hardware/software co-design
• Models of computation ensure reliable system communication