The 10 Practical Steps to Model and Design a Complex SoC: Insights from Aion Silicon

In the fast-evolving world of semiconductor design, creating a complex System-on-Chip (SoC) requires meticulous planning to ensure performance, power efficiency, and cost-effectiveness. Aion Silicon’s white paper, authored by Piyush Singh, outlines a streamlined methodology that leverages advanced modeling to bridge the gap from abstract concepts to silicon-ready specifications. Drawing on proprietary tools built atop EDA solutions from Arm and Synopsys, the paper emphasizes early architectural validation to mitigate risks and accelerate time-to-market. This approach is particularly vital for domains like AI, automotive, and high-performance computing, where SoCs integrate diverse components such as CPUs, GPUs, DSPs, and custom IP.

The white paper begins with an overview of SoC modeling’s role in preempting design flaws. Before placing any transistors, accurate models assess key metrics like bandwidth, latency, and Network-on-Chip (NoC) configuration. Aion Silicon’s custom modeling flow enhances vendor tools with extensive tweakable settings, enabling rapid iterations. Unlike traditional spreadsheet-based methods that take months, this flow delivers insights in days, allowing quick evaluation of variants to match customer use cases.

A core section explains how an ASIC evolves from an abstract view, depicted as application tasks on initiators (hardware blocks generating traffic) and targets (memory receivers), to a detailed specification. Central to this is the interconnect fabric, which connects compute and memory elements. Its design remains fluid until floor planning, influenced by timing constraints and die layout. Modeling provides a starting point, refining the NoC iteratively.

The paper highlights modeling’s advantages: estimating architecture, playing “what-if” scenarios, and enabling early software development. It categorizes modeling types, from dataflow (MATLAB / Python / C++ algorithms without timing) to loosely timed (for software prototyping) and approximately timed/fast timed models (ideal for exploration with transaction-level tracing). Cycle-accurate RTL simulations, while precise, are too slow for initial analysis.

Performance exploration is deemed essential because IP blocks, validated in isolation, face real-world constraints when integrated. Other blocks’ traffic patterns impact interconnect and memory, necessitating simulations to size subsystems appropriately.

The heart of the white paper is the “10 Steps to Architecture Success,” a phased approach breaking down complexity. The first four steps are analytical, often spreadsheet-based:

1. System OI Analysis: Examine input/output dataflows, including burstiness, latency, timing, and formatting to determine buffer needs.
2. Processing Analysis: Decompose algorithms into sub-tasks, grouping functionalities (e.g., MPEG decode and image analysis).
3. IP Analysis: Identify third-party IP blocks, incorporating datasheet details on memory and compute requirements for accurate modeling.
4. Data Interchange Analysis: Decide data exchange methods—on-chip SRAM/FIFO for small data or external DDR for large—based on size and access frequency.

The remaining steps shift to simulation:

5. Workflow Model (Transactional): Create software representations of algorithm stages as simulation objects (e.g., green boxes in diagrams) with latency/processing settings, connected by channels for sequencing.
6. Simulate to Verify Processing: Run simulations to visually confirm algorithm sequencing using modeling tools’ visualization features.
7. Quantify Data Interchange: Model hardware with Virtual Processor Units (VPUs) and local memory, defining communication domains and verifying configurations.
8. Data Physical Exchange: Remodel memory as external via a common controller, enhancing connectivity accuracy.
9. Implement Interconnect: Add NoC fabric, replacing direct connections, and evaluate timing/performance impacts, iterating as needed.
10. Optimize Performance: Adjust settings to identify bottlenecks, reduce latency, and improve throughput through quick simulations (minutes to hours).

These steps progressively refine models, eliminating dead ends and focusing resources logically. The paper concludes with Aion Silicon’s profile: founded in 2002, it offers end-to-end ASIC/SoC services across global centers, emphasizing first-time-right silicon.

Bottom line: This methodology underscores modeling’s transformative power in SoC design, reducing project risks and fostering innovation. By integrating custom flows with established EDA tools, Aion Silicon empowers designers to deliver optimized chips efficiently, proving that a structured path from abstraction to reality is key to semiconductor success.

See more AION Silicon Whitepapers here.

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