Learn how to measure and improve the accuracy and efficiency of your SoC simulation models and algorithms. Discover the trade-offs, challenges, and best practices for SoC simulation.

Multi-level simulation allows different levels of abstraction (e.g., cycle-accurate, transaction-level) to be used together, balancing accuracy and speed. We employed multi-level simulation to optimise the balance between detailed accuracy and simulation speed. For instance, while simulating the entire SoC, we used high-level transaction models for the less critical components and cycle-accurate models for critical paths like the CPU and memory subsystem. This approach enabled us to run comprehensive simulations more efficiently without sacrificing detail where it mattered most. Multi-level simulation allowed us to achieve a practical balance, enhancing both accuracy and efficiency.

How do you measure and improve the accuracy and efficiency of SoC simulation models and algorithms?

System on a Chip (SoC) is a complex integrated circuit that combines multiple functions and components on a single chip, such as processors, memory, peripherals, and interfaces. SoC simulation is a crucial step in the design and verification of SoC, as it allows engineers to test and validate the functionality, performance, and power consumption of the chip before fabrication. However, SoC simulation also poses many challenges, such as the accuracy and efficiency of the simulation models and algorithms. In this article, we will discuss how to measure and improve these aspects of SoC simulation and why they are important for the success of SoC projects.

1 Accuracy of SoC simulation models and algorithms

Accuracy refers to how well the simulation models and algorithms represent the actual behavior and characteristics of the SoC and its components. Accuracy is essential for ensuring the correctness and reliability of the SoC design and avoiding costly errors and bugs. To measure the accuracy of SoC simulation models and algorithms, engineers can use various methods, such as comparing the simulation results with the expected outcomes, using reference models or golden models that have been verified by other means, or applying formal methods that can prove the correctness of the models and algorithms mathematically.

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Santhosh Kumar Rethinagiri

System Engineering | System Modelling | System Innovation | Functional and Senior Manager @ Infineon Technologies
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SoC simulations can be a balancing act (think tightrope walk!). We need precise models to predict chip behavior, but super-detailed ones take forever! The key is finding the sweet spot: accurate enough to catch bugs before disaster strikes (think runaway phone overheating!), but fast enough to keep things on schedule. Imagine designing a smartphone chip - a quick model helps explore features early on, while a more detailed one ensures flawless performance before millions of units hit the market.

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2 Efficiency of SoC simulation models and algorithms

Efficiency refers to how fast and resource-efficient the simulation models and algorithms are. Efficiency is important for reducing the time and cost of SoC simulation and enabling faster iterations and feedback. To improve the efficiency of SoC simulation models and algorithms, engineers can use various techniques, such as optimizing the level of abstraction and detail of the models, using parallel or distributed simulation platforms that can leverage multiple cores or nodes, or applying smart simulation strategies that can focus on the most critical or relevant parts of the SoC.

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Santhosh Kumar Rethinagiri

System Engineering | System Modelling | System Innovation | Functional and Senior Manager @ Infineon Technologies
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Simulating SoCs takes time, and who wants to wait forever? That's where efficiency comes in. We need models that run fast and don't gobble up resources. Think of it like a race car - lightweight and optimized for speed. Engineers use tricks like the right level of detail and clever simulation strategies to get those simulations zipping along, saving time and money for faster chip design!

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3 Trade-offs between accuracy and efficiency

While accuracy and efficiency are both desirable goals for SoC simulation, they often conflict with each other. For example, increasing the accuracy of the simulation models and algorithms may require more computation time and memory, while increasing the efficiency may compromise the fidelity and completeness of the simulation results. Therefore, engineers need to balance the trade-offs between accuracy and efficiency depending on the objectives and constraints of the SoC simulation project. For instance, they may use different levels of accuracy and efficiency for different stages or aspects of the SoC design and verification process, such as using high-accuracy models for functional verification and low-accuracy models for performance analysis.

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Santhosh Kumar Rethinagiri

System Engineering | System Modelling | System Innovation | Functional and Senior Manager @ Infineon Technologies
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Simulating SoCs is a juggling act! Super-accurate models are fantastic for catching bugs, but they can be slow as molasses. On the other hand, lightning-fast simulations are great for quick checks, but they might miss hidden issues. The sweet spot lies in finding the right balance for each stage. Imagine designing a self-driving car - early simulations might focus on core functionality (think steering and braking) with simpler models, while later stages use super-detailed models to ensure everything runs perfectly under any condition. By cleverly choosing accuracy and efficiency, engineers can design amazing chips

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4 Challenges of SoC simulation models and algorithms

Despite the advances in SoC simulation technologies and tools, engineers still face many challenges when developing and using SoC simulation models and algorithms. These include the complexity and diversity of SoC architectures and components, which require sophisticated and adaptable models to capture the interactions and dependencies among them. Additionally, scalability and compatibility of SoC simulation platforms and frameworks must be considered, as they need to support large-scale and heterogeneous SoC designs while enabling seamless integration and communication between different models and tools. Finally, the quality and availability of SoC simulation data and benchmarks are essential for validating and comparing the accuracy and efficiency of the models and algorithms.

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Santhosh Kumar Rethinagiri

System Engineering | System Modelling | System Innovation | Functional and Senior Manager @ Infineon Technologies
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SoC simulation: a double-edged sword! Powerful tools help us design chips, but challenges remain. First, SoCs are like intricate puzzles - tons of unique parts that need to work together perfectly. Simulating them requires flexible models to capture these interactions. Then, imagine building a giant city - all the different simulation tools need to work seamlessly together, no matter how big or complex the chip design gets. Finally, good data is king! We need solid benchmarks to check how accurate and efficient our simulations are. Despite the hurdles, engineers are constantly innovating to create the chips of tomorrow!

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5 Best practices for SoC simulation models and algorithms

To overcome challenges and achieve high-quality and high-performance SoC simulation, engineers can employ best practices for developing and using SoC simulation models and algorithms. A modular and hierarchical approach can simplify the design and verification process, while a systematic and rigorous methodology can ensure the consistency and completeness of the models and algorithms. Additionally, leveraging existing standards and libraries can enhance interoperability, portability, and reduce development time.

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Cmdr (Dr.⁹) Reji Kurien Thomas , FRSA, MLE℠

I Empower Sectors as a Global Tech & Business Transformation Leader| Stephen Hawking Award 2024| Harvard Leader | UK House of Lord's Awardee | Fellow Royal Society | CyberSec | CCISO CISM CCNP-S CEH
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Multi-level simulation allows different levels of abstraction (e.g., cycle-accurate, transaction-level) to be used together, balancing accuracy and speed. We employed multi-level simulation to optimise the balance between detailed accuracy and simulation speed. For instance, while simulating the entire SoC, we used high-level transaction models for the less critical components and cycle-accurate models for critical paths like the CPU and memory subsystem. This approach enabled us to run comprehensive simulations more efficiently without sacrificing detail where it mattered most. Multi-level simulation allowed us to achieve a practical balance, enhancing both accuracy and efficiency.

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Santhosh Kumar Rethinagiri

System Engineering | System Modelling | System Innovation | Functional and Senior Manager @ Infineon Technologies
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Conquering SoC simulation involves some clever tactics. Building models in bite-sized, organized chunks (think modular kitchen cabinets) makes everything easier to manage and test. A structured approach, like a meticulous recipe, ensures consistency and catches errors early on. Plus, reusing existing tools and libraries is like using pre-made ingredients - saves time and effort! By following these best practices, engineers can whip up high-quality, high-performance SoC simulations that pave the way for awesome chip designs!

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Cmdr (Dr.⁹) Reji Kurien Thomas , FRSA, MLE℠

I Empower Sectors as a Global Tech & Business Transformation Leader| Stephen Hawking Award 2024| Harvard Leader | UK House of Lord's Awardee | Fellow Royal Society | CyberSec | CCISO CISM CCNP-S CEH
Report contribution
Benchmarking Against Real Hardware- In a recent SoC project, we benchmarked our simulation models against actual hardware performance. This comparison highlighted discrepancies and guided us to refine our models for greater accuracy. Incremental Model Refinement- Over the years, I've adopted an iterative approach. By progressively refining simulation models based on test results, we've significantly improved both accuracy and efficiency. Utilising Advanced Simulation Tools- Leveraging advanced tools like Synopsys VCS and Cadence Palladium has been crucial. These tools offer sophisticated features that enhance the fidelity of our simulations

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How do you measure and improve the accuracy and efficiency of SoC simulation models and algorithms?

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1 Accuracy of SoC simulation models and algorithms

2 Efficiency of SoC simulation models and algorithms

3 Trade-offs between accuracy and efficiency

4 Challenges of SoC simulation models and algorithms

5 Best practices for SoC simulation models and algorithms

6 Here’s what else to consider

System on a Chip (SoC)

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