EDA TIMES

Electronic Design Automation for AI era!

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  • Revolutionizing SoC Design with 3D Heterogeneous Integration

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    Insights

    • Cadence offers an integrated 3D-IC design flow enabling seamless chiplet and multi-die integration.
    • Their UCIe PHY, Controller, and VIP support combining diverse dies from various fabs and technologies.
    • Solutions target automotive, data center, and other verticals requiring advanced packaging and performance optimization.
    • Cadence’s tools address power, performance, area, timing closure, and complex simulation challenges.
    • Comprehensive training and support resources help designers accelerate chiplet-based SoC development.

    The advancement of 3D heterogeneous integration is transforming system-on-chip (SoC) design by enabling the seamless combination of multiple chiplets, including 2D and 2.5D dies, sourced from different fabs and packaging technologies. Cadence Design Systems leads this space by providing an integrated flow for chiplet and 3D-IC designs that serve automotive, data center, and various other industries.

    The company’s Cadence UCIe PHY, Controller, and verification IP facilitate on-package mix-and-match chiplet configurations, allowing designers to optimize power, performance, and area (PPA) while achieving timing closure in multi-chiplet environments. Cadence’s comprehensive offerings cover design IP, verification, system-level analysis, and multi-die package implementation, backed by over 25 years of experience in advanced packaging.

    These solutions address key challenges such as electromagnetic, thermal, and electromechanical simulations to ensure robust designs under diverse operating conditions. Through extensive educational resources and a supportive community, Cadence empowers engineers to accelerate innovation in disaggregated chip development, tackling physical constraints and cost issues at advanced semiconductor nodes effectively.

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  • PsiQuantum Secures $1 Billion to Build Fault-Tolerant Quantum Computers

    PsiQuantum Secures $1 Billion to Build Fault-Tolerant Quantum Computers

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    Insights

    • PsiQuantum raised $1 billion in Series E funding, valuing the company at $7 billion.
    • The company aims to build million-qubit, fault-tolerant quantum computers using photonic technology.
    • PsiQuantum leverages high-volume semiconductor manufacturing and integrated Barium Titanate (BTO) electro-optic switches.
    • New funding supports scaling production, building utility-scale quantum sites in Brisbane and Chicago, and advancing cooling and networking systems.
    • Strategic partnerships include NVIDIA and major investors like BlackRock, Temasek, and Baillie Gifford.

    PsiQuantum has announced a monumental $1 billion Series E funding round, backed by leading investors such as BlackRock, Temasek, and Baillie Gifford, pushing its valuation to $7 billion. This capital will accelerate the company’s development of commercially viable, fault-tolerant quantum computers at a million-qubit scale, a significant engineering challenge the company is uniquely positioned to solve by leveraging photonic quantum technology and mass semiconductor manufacturing.

    Central to PsiQuantum’s approach is the integration of Barium Titanate (BTO), a powerful electro-optic material enabling ultra-high-performance optical switches critical for scaling quantum systems. The company manufactures these photonic chips at GlobalFoundries’ Fab 8 facility and produces BTO wafers in its California labs. Their cooling solutions and networking techniques aim to overcome traditional quantum computing barriers, avoiding bulky cryostats and enabling scalable, data-center-like architectures.

    With partnerships including NVIDIA, PsiQuantum is not only advancing hardware but also exploring software integration and quantum algorithms. The new funding will support building utility-scale quantum computing sites in Brisbane and Chicago and scaling production to meet anticipated commercial demand. Industry leaders see PsiQuantum’s efforts as positioning it at the forefront of a quantum revolution poised to transform computing beyond AI’s current capabilities.

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  • NVIDIA’s Vision: Building the Future AI Factories with Digital Twins

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    At the recent AI Infrastructure Summit, NVIDIA introduced a groundbreaking paradigm: transforming traditional data centers into highly integrated AI factories. Moving beyond its core chip business, NVIDIA is partnering with major technology and infrastructure companies to co-engineer facilities optimized for the intensive power and cooling demands of AI workloads. This initiative embraces a system-level approach, unifying compute, power, cooling, and orchestration into a seamlessly designed infrastructure. Central to this vision is the creation of digital twins — virtual replicas of AI factory environments — built on the NVIDIA Omniverse platform. These twins enable pre-construction simulation and continuous operational management, ensuring maximum efficiency and reliability. By using simulation-ready digital assets and adopting the open standard OpenUSD framework, NVIDIA and its partners can model every component from power grids to facility cooling systems in unprecedented detail. Collaborators including Siemens, Jacobs, and Schneider Electric bring decades of infrastructure expertise for gigawatt-scale energy delivery and sustainable operations. When fully realized, this AI factory blueprint will foster real-time cross-industry collaboration through APIs and digital assets, ushering in a new era of composable, resilient, and scalable AI infrastructure designed specifically for the next generation of AI computing demands.

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    Insights

    • NVIDIA is pioneering a new AI factory concept by integrating data center infrastructure with AI-optimized systems for power, cooling, and orchestration.
    • The initiative uses digital twins and simulation via the NVIDIA Omniverse platform to design, optimize, and operate AI factories before physical construction.
    • Industry leaders like Siemens, Jacobs, Schneider Electric, and GE Vernova collaborate to provide expertise in power delivery, cooling, and infrastructure integration at gigawatt-scale.
    • By co-designing infrastructure and compute platforms, NVIDIA enables system-level efficiency that reduces energy waste and improves reliability in AI workloads.
    • OpenUSD-standard simulation assets and APIs will allow partners to engage in real-time collaboration, promoting scalable and resilient AI factory ecosystems.
    At the recent AI Infrastructure Summit, NVIDIA introduced a groundbreaking paradigm: transforming traditional data centers into highly integrated AI factories. Moving beyond its core chip business, NVIDIA is partnering with major technology and infrastructure companies to co-engineer facilities optimized for the intensive power and cooling demands of AI workloads. This initiative embraces a system-level approach, unifying compute, power, cooling, and orchestration into a seamlessly designed infrastructure. Central to this vision is the creation of digital twins — virtual replicas of AI factory environments — built on the NVIDIA Omniverse platform. These twins enable pre-construction simulation and continuous operational management, ensuring maximum efficiency and reliability. By using simulation-ready digital assets and adopting the open standard OpenUSD framework, NVIDIA and its partners can model every component from power grids to facility cooling systems in unprecedented detail. Collaborators including Siemens, Jacobs, and Schneider Electric bring decades of infrastructure expertise for gigawatt-scale energy delivery and sustainable operations. When fully realized, this AI factory blueprint will foster real-time cross-industry collaboration through APIs and digital assets, ushering in a new era of composable, resilient, and scalable AI infrastructure designed specifically for the next generation of AI computing demands.

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  • IBM and AMD Unite to Pioneer Quantum-Centric Supercomputing

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    Insights

    • IBM and AMD are collaborating to create hybrid quantum-centric supercomputing architectures combining quantum computers with high-performance classical computing.
    • This approach leverages quantum computing’s unique qubits alongside AMD’s CPUs, GPUs, and AI accelerators to tackle complex problems in fields like drug discovery and materials science.
    • The partnership aims to develop scalable, open-source platforms and demonstrate hybrid quantum-classical workflows later this year.
    • IBM’s vision includes achieving fault-tolerant quantum computing by decade’s end, with AMD technologies potentially enabling real-time error correction.
    • Integrating quantum and classical computing could drastically accelerate scientific discovery and innovation well beyond current computational limits.

    IBM and AMD have announced a strategic collaboration to develop next-generation computing architectures that integrate quantum computing with high-performance classical computing, termed quantum-centric supercomputing. By combining IBM’s expertise in building world-leading quantum systems with AMD’s powerful CPUs, GPUs, and AI accelerators, the companies aim to create hybrid platforms capable of solving complex problems that classical computers alone cannot tackle. Quantum computers, through qubits that exploit quantum mechanics, can simulate molecular and atomic behaviors, while classical supercomputers handle AI-driven data analysis. Together, these capabilities offer unprecedented speed and scale in fields such as drug discovery, materials science, optimization, and logistics. The partnership plans to demonstrate hybrid quantum-classical workflows this year and advance open-source ecosystems like Qiskit to accelerate algorithm development. Additionally, AMD’s technologies may support critical real-time error correction needed for fault-tolerant quantum computing, a major milestone IBM aims to achieve by the end of this decade. This collaboration marks a significant leap toward seamlessly integrating quantum and classical computing, unlocking new frontiers in scientific innovation and computational power. For more info. visit: https://www.amd.com/en/newsroom/press-releases/2025-8-26-ibm-and-amd-join-forces-to-build-the-future-o.html

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  • Physical AI: Revolutionizing Real-World Robotics and Human Interaction

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    Insights

    • Physical AI integrates robotics and machine learning to function autonomously in dynamic real-world environments, extending human capabilities.
    • The development of physical AI marks the next major phase after digital infrastructure and agentic AI, with trillion-dollar industry potential.
    • Successful physical AI emphasizes seamless human-machine collaboration, augmenting productivity rather than replacing humans.
    • Ethical considerations, including transparency, trust, and equitable access, are critical as physical AI systems become more widespread.
    • Real-world applications like healthcare robotics (e.g., Moxi) show how physical AI fills labor gaps and improves operational efficiency.

    Physical AI represents a transformative step in artificial intelligence, shifting focus from digital-only applications to intelligent systems that operate autonomously in the physical world. This emerging technology blends robotics and machine learning to create robots, drones, and autonomous vehicles capable of sensing, processing, and responding to complex environments. A panel of experts at SXSW 2025 highlighted how physical AI differs from traditional AI, emphasizing its vertical, domain-specific nature and vast industrial potential spanning healthcare, manufacturing, logistics, and daily life. Industry leaders like Dr. Anirudh Devgan explain that physical AI is the forthcoming phase in AI evolution, poised to unlock trillion-dollar markets by enhancing real-world systems beyond current data-centric models. Experts including Amazon’s chief roboticist Tye Brady stress that physical AI should amplify human abilities through seamless integration rather than automation-driven replacement. Innovations such as hospital assistant robots demonstrate tangible benefits, alleviating labor shortages and increasing efficiency. However, ethical concerns around transparency, collaboration, and accountability underscore the need for coordinated global efforts to govern this technology responsibly. As physical AI matures, it promises to revolutionize productivity while demanding thoughtful deployment to ensure it serves society broadly and ethically. For more info. visit: https://community.cadence.com/cadence_blogs_8/b/corporate-news/posts/how-physical-ai-integration-is-transforming-the-real-world

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  • The Rise of Physical AI: Transforming Real-World Robotics and Human Collaboration

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    Insights

    • Physical AI integrates machine learning with robotics to create systems that sense and respond to real-world environments, enhancing human productivity across industries.
    • The evolution of AI is entering a new phase—physical AI—expected to unlock trillion-dollar markets over the next 2 to 7 years, followed by sciences AI in the longer term.
    • Human-robot collaboration is key; effective physical AI systems work seamlessly in the background, amplifying human capabilities rather than replacing jobs.
    • Ethical, transparent, and global collaboration is crucial to ensure physical AI benefits society equitably and maintains trust.
    • Healthcare is an early leader in adopting physical AI, with robots like Moxi easing labor shortages and freeing professionals to focus on patient care.
    Physical AI is revolutionizing how machines and humans interact by merging robotics with artificial intelligence to operate effectively in real-world settings. At SXSW 2025, top leaders including Dr. Anirudh Devgan and Sir Tim Berners-Lee discussed this transformative technology now moving from digital infrastructure toward domain-specific, physical applications such as autonomous vehicles, drones, and humanoid assistants. Unlike early AI focused on data and computational power, physical AI promises to unlock vast economic potential by embedding intelligent robotics into industries like healthcare, manufacturing, and logistics. Tye Brady of Amazon highlighted the importance of designing these systems to augment human abilities rather than replace them, enabling a “symphony” of human-machine collaboration that quietly boosts efficiency. Healthcare is already benefiting from robots like Moxi, which assist medical staff by handling routine tasks, addressing labor shortages and improving care delivery. However, challenges around trust, ethics, and global cooperation remain critical to ensuring equitable and safe adoption. Overall, physical AI is poised to expand the frontiers of productivity and innovation, signaling a pivotal shift toward the next era of AI-driven technological advancement. For more info. visit: https://community.cadence.com/cadence_blogs_8/b/corporate-news/posts/how-physical-ai-integration-is-transforming-the-real-world

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  • Intel Announces Leadership Appointments to Strengthen Core Business and Foundry Strategy

    Intel Announces Leadership Appointments to Strengthen Core Business and Foundry Strategy

    Viz R.

    Intel Announces Leadership Appointments to Strengthen Core Business and Foundry Strategy

    Intel today announced several senior leadership appointments designed to strengthen its core product business, build a trusted foundry, and foster a stronger engineering culture across the company. The changes position the company to accelerate growth in data center, client computing, and custom silicon.

    Kevork Kechichian has joined as executive vice president and general manager of the Data Center Group (DCG), overseeing Intel’s data center activities in cloud and enterprise, including the Xeon processor family. He brings more than 30 years of experience, most recently serving as executive vice president of engineering at Arm, where he led technology development and the shift from IP licensing to full-stack solutions. He previously held senior engineering roles at NXP Semiconductors and Qualcomm. CEO Lip-Bu Tan said Kechichian’s strategic vision, technical depth, and operational rigor will help Intel capture growth opportunities in the data center market.

    Jim Johnson has been named senior vice president and general manager of the Client Computing Group (CCG), after serving in an interim role. A 40-year Intel veteran, Johnson has led multiple units and will drive innovation and growth across PC and edge ecosystems as Intel prepares to launch a new generation of products. Tan highlighted his steady leadership and trusted industry relationships.

    Srini Iyengar, SVP and Fellow, will lead Intel’s newly formed Central Engineering Group, including horizontal engineering functions and a new custom silicon business for external customers. Iyengar joined Intel from Cadence Design Systems and brings deep expertise in custom silicon and collaboration with hyperscale data center customers. Tan said the role aligns innovation and execution to serve customers.

    Naga Chandrasekaran will expand his leadership of Intel Foundry to include Foundry Services, creating a more integrated structure spanning technology development, manufacturing, and go-to-market. Kevin O’Buckley will continue as SVP and GM of Foundry Services, reporting to Chandrasekaran.

    Michelle Johnston Holthaus, chief executive of Intel Products, will depart after more than three decades with the company and will serve as a strategic advisor to ensure a smooth transition. Tan thanked her for her transformative leadership.
    For more info. visit: https://newsroom.intel.com/corporate/intel-announces-key-leadership-appointments

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  • Synopsys Expands GenAI Copilot Capabilities to Accelerate Chip Design

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    Synopsys Expands GenAI Copilot Capabilities to Accelerate Chip Design

    Synopsys announced an expansion of its Synopsys.ai Copilot GenAI capabilities to speed semiconductor design, help handle more complex designs, and boost engineering velocity amid a workforce shortage. The company positions AI as a core element of modern chip design, using reinforcement learning and GenAI to optimize silicon performance, improve efficiency, and accelerate time-to-market across its Synopsys.ai suite. The expanded Copilot features, covering assistive and creative tasks across the design flow, are already in use with early access customers and are delivering measurable gains in design quality and productivity, shrinking workflows from days to hours and from hours to minutes.

    Generative AI-powered Copilot capabilities now include New Ansys Engineering Copilot, which deepens GenAI simulation capabilities. Ansys, now part of Synopsys, recently introduced Ansys Engineering Copilot—a virtual assistant that helps shorten learning curves and boost engineer productivity when using Synopsys simulation tools. The release also updates Ansys SimAI, a physics-agnostic tool blending the predictive accuracy of simulation with AI speed, and SimAI is integrated with Ansys optiSLang to accelerate dataset creation and AI training for broader design variation exploration and shorter development cycles.

    AgentEngineer Technology Under Development—First Prototype Demonstrated highlights the next frontier. Synopsys’ GenAI capabilities underpin AgentEngineer, designed to enable progressive autonomous execution in engineering workflows. A prototype was showcased at DAC 2025 in collaboration with Microsoft Discovery, signaling a new paradigm for agentic AI. Synopsys envisions advancing AgentEngineer from single-agent steps to multi-agent collaboration, then dynamic flow optimization and autonomous decision making.

    Learn more at synopsys.com/ai.html.
    For more info. visit: https://news.synopsys.com/2025-09-03-Synopsys-Announces-Expanding-AI-Capabilities-for-its-Leading-EDA-Solutions

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  • Siemens Unveils AI-Enhanced EDA Toolset at DAC 2025

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    Siemens Unveils AI-Enhanced EDA Toolset at DAC 2025

    At DAC 2025 in San Francisco, Siemens Digital Industries Software introduced an AI-enhanced EDA toolset designed to accelerate semiconductor and PCB design workflows. The centerpiece is a purpose-built EDA AI system that combines secure, generative and agentic AI with deep customization and seamless integration across the entire EDA flow. Siemens frames the system as a strategic investment to help design teams handle increasing complexity and bring breakthrough designs to market faster.

    The EDA AI system supports open, customizable workflows: customers can ingest their own EDA data, tailor AI-driven processes, and deploy AI where it adds the most value. Deployment is flexible (on-premises or cloud) with enterprise-grade security, robust access controls, and a centralized multimodal data lake that supports a range of AI models, from large language models to traditional ML and reinforcement learning.

    Siemens is leveraging NVIDIA technologies to accelerate EDA tasks, including NVIDIA NIM microservices for scalable inference across cloud and on-premises, and the Llama Nemotron for enhanced context reasoning and tool-calling. Industry perspectives from NVIDIA note that AI agents can significantly boost productivity across layout optimization, simulation, and verification.

    Key portfolio components highlighted include:
    – Aprisa AI: integrated into RTL-to-GDS flow, offering AI-driven design exploration, PPA optimization, and a 10x productivity boost, with 3x faster tapeout and around 10% better PPA.
    – Calibre Vision AI: chip-integration signoff with clustering, state bookmarks, and collaboration enhancements, integrated into existing layout viewers.
    – Solido: generative and agentic AI across the custom IC process from schematic to verification, enabling substantial productivity gains.

    Availability is currently in early access across Siemens EDA offerings, with more details on Siemens’ EDA AI pages.

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  • Cadence to Acquire Hexagon’s Design & Engineering Unit to Boost Multiphysics System Design

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    Cadence to Acquire Hexagon’s Design & Engineering Unit to Boost Multiphysics System Design

    Cadence Design Systems announced a definitive agreement to acquire the Design & Engineering (D&E) business of Hexagon AB, including MSC Software, for about €2.7 billion. The deal funds 70% in cash and 30% in Cadence common stock to Hexagon, and is expected to close in the first quarter of 2026, subject to regulatory approvals.

    The acquisition accelerates Cadence’s Intelligent System Design strategy by expanding its System Design & Analysis portfolio and strengthening its presence in structural analysis alongside its existing electromagnetics, electrothermal, and CFD capabilities. Hexagon D&E brings flagship multiphysics solvers, notably MSC Nastran and Adams, which are industry standards for structural and multibody dynamics simulation. These tools will augment Cadence’s capabilities and enable a unified, end-to-end multiphysics platform that supports earlier, more integrated analyses during the design cycle.

    This move enhances Cadence’s reach into aerospace, automotive, robotics, and industrial applications, complementing its Beta CAE acquisition from 2024. The combined solution set aims to drive convergence of electrical and mechanical design—supporting robotics, autonomous systems, physical AI, and electrified vehicle development. The deal also broadens Cadence’s customer base to major OEMs and Tier 1 suppliers including Volkswagen Group, BMW, Toyota, Lockheed Martin, BAE, and Boeing.

    Hexagon D&E generated about $280 million in revenue in 2024 and employs over 1,100 people across global sites, with strong R&D, sales, and support teams. The transaction signals Cadence’s push to offer comprehensive, converged simulation for tomorrow’s complex systems.

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  • Synopsys Reports Q3 2025 Results; Ansys Merger Drives Transformation and 2025 Outlook

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    Synopsys Reports Q3 2025 Results; Ansys Merger Drives Transformation and 2025 Outlook

    Synopsys, Inc. (Nasdaq: SNPS) reported its third quarter of fiscal year 2025 results with revenue of about $1.74 billion, up from $1.53 billion a year earlier. The company framed Q3 as a transformational quarter driven by the closing of the Ansys acquisition, expanding its portfolio and AI-powered product opportunities, while noting weakness in the Design IP business offset strength in Design Automation. GAAP net income was $242.5 million ($1.50 per diluted share) versus $425.9 million ($2.73) in the prior year’s quarter. On a non-GAAP basis, net income rose to $548.9 million ($3.39 per diluted share) from $535.5 million ($3.43) a year ago.

    Business segments show Design Automation generating $1,312.1 million and Design IP $427.6 million in quarterly revenue (about 75.4% and 24.6% of total, respectively). Adjusted operating income by segment was $583.8 million for Design Automation (44.5% margin) and $86.0 million for Design IP (20.1% margin).

    For the fourth quarter and full fiscal year 2025, Synopsys provided targets: revenue of $2.23–$2.26 billion for Q4 and $7.03–$7.06 billion for FY2025; GAAP expenses $2.115–$2.139 billion and non-GAAP expenses $1.440–$1.450 billion; non-GAAP tax rate of 16%; outstanding shares about 187–188 million. Non-GAAP EPS is guided to $2.76–$2.80 for Q4 and $12.76–$12.80 for FY2025; GAAP EPS is guided to a negative range for Q4 and $5.03–$5.16 for FY2025. Operating cash flow is projected near $1.13 billion and free cash flow about $0.95 billion, with capital expenditures around $180 million.

    Notes: Synopsys completed the Software Integrity sale in 2024 and acquired Ansys in 2025. The company also cautions that forward-looking targets are subject to risks including macro conditions and export controls.

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