AI-Powered Transformation in EDA

The integration of artificial intelligence (AI) into Electronic Design Automation (EDA) is revolutionizing chip design, addressing the critical shortage of skilled engineers and accelerating the development process. As Jeff Dyck, Senior Director of Engineering at Siemens EDA, explains in a recent DACtv presentation, AI is being embedded into every facet of EDA tools to achieve unprecedented speed-ups while maintaining accuracy and reliability.

The semiconductor industry faces a significant challenge: the demand for chips far exceeds the supply of engineers capable of designing them. Traditional methods are too slow to bridge this gap, necessitating innovative solutions. AI offers the potential for dramatic improvements, with Siemens EDA leveraging it to achieve 10x, 100x, and even million-fold speed-ups in various design processes. However, Dyck emphasizes that speed alone is insufficient—accuracy, verifiability, generality, robustness, and usability are critical for production-ready tools.

Siemens EDA’s journey with AI began with Solido Design Automation, acquired in 2017, which pioneered production-quality AI tools as early as 2006. Initially, Solido experimented with partially reliable AI prototypes that delivered impressive speed-ups but lacked verifiability. Recognizing the importance of trust in engineering, they developed a tiered approach to AI tool maturity. Level 0 represents traditional, slow but reliable tools. Level 1 includes fast but unverifiable prototypes. Level 2 introduces self-verifying, accuracy-aware models, while Level 3, the gold standard for production, incorporates adaptive learning to ensure correct results even for new designs.

A breakthrough came in 2008 with Solido’s High Sigma Monte Carlo tool, the first Level 3 AI tool in chip design. This tool tackled the verification of replicated components, such as memories and standard cells, achieving million-fold speed-ups over traditional Monte Carlo methods while maintaining perfect accuracy and self-verification. This success established Solido as a sustainable company and set a precedent for Siemens EDA’s AI strategy.

The “Solido-style” adaptive AI approach starts with minimal circuit knowledge, running sparse simulations to build an initial model. It then iteratively refines this model, focusing simulations on critical areas like high-sigma tails or low-gain regions, achieving engineering tolerances (e.g., 2% accuracy or two picoseconds) efficiently. This method avoids wasteful simulations, prioritizing areas of interest and incorporating self-verification to ensure reliability. Subsequent tools, like Fast PVT and Cell Optimizer, applied this approach to optimize process, voltage, and temperature corners and standard cell designs, respectively, delivering fully verified results.

In 2023, Siemens EDA introduced additive learning, which reuses knowledge from previous runs to accelerate subsequent iterations. This technology automatically verifies whether prior models remain valid, adapting as needed without human intervention. The recent launch of Solido Sim, including Solido SPICE, FastSPICE, and LibSPICE, integrates these AI techniques directly into SPICE simulators, achieving significant speed-ups, such as 16x faster high-sigma library verification.

Beyond Solido, Siemens EDA is embedding AI across its product lines, including Veloce, Questa, Tessent, Calibre, and HyperLynx, delivering improvements like 50% time reductions and 100x speed-ups. A centralized AI team accelerates this innovation, developing foundational technologies to enhance all EDA tools. Dyck notes that while off-the-shelf AI techniques like scikit-learn are used, Siemens EDA also builds custom modeling technologies to handle complex tasks, such as 300,000-dimensional models, ensuring scalability and precision.

Looking forward, Siemens EDA is exploring large language models (LLMs) and retrieval-augmented generation (RAG) to further enhance EDA processes, particularly for chip design-specific applications. This strategic investment in AI, combined with a focus on delivering verifiable, production-ready tools, positions Siemens EDA at the forefront of the industry’s transformation, promising faster, more reliable chip design to meet global demand.

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