Presentation
Bridging Quantum, AI, and EDA: The Next Frontier of Design Automation
DescriptionQuantum technologies are rapidly transitioning from academic curiosity to practical enablers of next-generation electronic design automation (EDA). Yet the real opportunity lies not only in quantum computing itself, but in the convergence of quantum simulation, materials modeling, AI-native design, and system-level automation. This panel brings together leaders across quantum hardware, software, and industrial design workflows to examine how quantum technologies—paired with frontier AI—will transform the semiconductor and system-design landscape over the next decade.
Today's design challenges have outgrown classical scaling curves. Whether optimizing advanced node devices, discovering novel materials, modeling parasitic effects, or designing 3D-IC systems with extreme multiphysics coupling, classical simulation methods are straining under exponential complexity. Emerging quantum-accelerated approaches offer breakthrough potential: Hamiltonian-based solvers for nanoscale transport; quantum-enhanced simulation for chemical and materials discovery; quantum optimization methods for scheduling, routing, and verification; and hybrid quantum-classical pipelines that integrate seamlessly with existing EDA flows.
At the same time, generative AI and large language models (LLMs) are redefining design productivity. The intersection—Quantum × AI × EDA—is creating a new paradigm where quantum simulation feeds AI-driven design agents, AI discovers optimal materials for quantum and classical devices, and EDA frameworks orchestrate end-to-end system exploration. This compounding loop is catalyzing a shift toward Materials Design Automation (MDA), automated device co-optimization, and rapid multi-physics exploration at atomic accuracy.
This panel will explore four key themes:
1. Quantum Simulation for Materials & Devices: How quantum-accurate modeling (AIMD, MLFF, QMC, variational quantum solvers) unlocks breakthroughs in semiconductors, batteries, photonics, and superconducting components.
2. Quantum Hardware and Software Stack Evolution: Practical roadmaps, error-correction thresholds, algorithmic readiness, and how near-term quantum systems can augment industrial design workflows.
3. AI-Native and LLM-Driven Design Automation: How foundation models, retrieval-augmented simulation, and autonomous design agents interface with quantum tools to accelerate PPA and manufacturability.
4. Industrial Adoption & ROI: What it will take for design teams—fabless, IDM, EDA vendors, and hyperscalers—to integrate quantum capabilities into real production flows.
The session will conclude with a forward-looking discussion on how quantum technologies may reshape the future of design automation—shifting the industry from traditional scaling to physics-accelerated, AI-co-designed innovation. Attendees will leave with a clear understanding of what's real, what's coming, and how to prepare their organizations for the quantum-enabled EDA era.
Today's design challenges have outgrown classical scaling curves. Whether optimizing advanced node devices, discovering novel materials, modeling parasitic effects, or designing 3D-IC systems with extreme multiphysics coupling, classical simulation methods are straining under exponential complexity. Emerging quantum-accelerated approaches offer breakthrough potential: Hamiltonian-based solvers for nanoscale transport; quantum-enhanced simulation for chemical and materials discovery; quantum optimization methods for scheduling, routing, and verification; and hybrid quantum-classical pipelines that integrate seamlessly with existing EDA flows.
At the same time, generative AI and large language models (LLMs) are redefining design productivity. The intersection—Quantum × AI × EDA—is creating a new paradigm where quantum simulation feeds AI-driven design agents, AI discovers optimal materials for quantum and classical devices, and EDA frameworks orchestrate end-to-end system exploration. This compounding loop is catalyzing a shift toward Materials Design Automation (MDA), automated device co-optimization, and rapid multi-physics exploration at atomic accuracy.
This panel will explore four key themes:
1. Quantum Simulation for Materials & Devices: How quantum-accurate modeling (AIMD, MLFF, QMC, variational quantum solvers) unlocks breakthroughs in semiconductors, batteries, photonics, and superconducting components.
2. Quantum Hardware and Software Stack Evolution: Practical roadmaps, error-correction thresholds, algorithmic readiness, and how near-term quantum systems can augment industrial design workflows.
3. AI-Native and LLM-Driven Design Automation: How foundation models, retrieval-augmented simulation, and autonomous design agents interface with quantum tools to accelerate PPA and manufacturability.
4. Industrial Adoption & ROI: What it will take for design teams—fabless, IDM, EDA vendors, and hyperscalers—to integrate quantum capabilities into real production flows.
The session will conclude with a forward-looking discussion on how quantum technologies may reshape the future of design automation—shifting the industry from traditional scaling to physics-accelerated, AI-co-designed innovation. Attendees will leave with a clear understanding of what's real, what's coming, and how to prepare their organizations for the quantum-enabled EDA era.
Event Type
Research Panel
TimeWednesday, July 2910:30am - 12:30pm PDT
LocationMtg Room 104A
Design