Cadence and TSMC Expand Certified Solutions for Artificial Intelligence and 3D-IC Chip Design

Cadence and TSMC deepen their partnership to advance Artificial Intelligence and 3D-IC chip innovations, focusing on new certified design solutions for TSMC´s latest A16 and N2P process technologies.

Cadence has announced a significant expansion of its collaboration with TSMC aimed at accelerating the development of 3D-IC and advanced-node chip technologies. Through ongoing certification of design flows and silicon-proven intellectual property, Cadence is reinforcing its commitment to supporting TSMC’s evolving process nodes, including the N2P, N5, and N3 families. This partnership facilitates a more streamlined path from chip design to silicon for applications spanning chiplets, system-on-chips (SoCs), advanced packaging, and three-dimensional integrated circuits.

The joint efforts encompass certified design tools and methodologies optimized for TSMC’s N2P and newly introduced A16 technologies. These advancements lay the groundwork for future nodes such as TSMC’s A14, while also expanding support for TSMC’s 3DFabric design and packaging ecosystem, which is key for next-generation 3D-IC innovations. Additionally, Cadence and TSMC are retroactively extending tool certification to cover TSMC’s N3C technology, building on established N3P design flows to enable broader adoption.

Cadence’s leadership in artificial intelligence chip design is underlined by its certified toolchain and optimized IP, including the TSMC9000 pre-silicon-validated DDR5 12.8G IP for the N2P node. The company’s digital, custom/analog, and thermal analysis solutions have also received certification for the N2P and A16 processes. Leveraging large language models and other advanced Artificial Intelligence-driven techniques, Cadence and TSMC continue to collaborate closely, driving the evolution of digital design flows needed for the complexity and performance demands of emerging semiconductor technologies.

73

Impact Score

FluxMem brings dynamic memory to large language model agents

FluxMem reframes memory for large language model agents as a dynamic graph that evolves with feedback, task variation, and long-term use. The approach is designed to reduce the brittleness of static memory systems and improve reliability in complex environments.

Microsoft and NVIDIA hint at N1X Windows 11 launch

Microsoft and NVIDIA signaled a joint Windows 11 push around the N1X, framing it as a new era of PC. The upcoming Arm chip is positioned to bring Copilot+ acceleration and challenge the fastest Windows processors in its class.

YouTube to automatically label Artificial Intelligence-generated videos

YouTube is shifting from voluntary disclosure to automated detection for significant photorealistic Artificial Intelligence-generated video content. Labels will become more visible across long-form videos and Shorts, with permanent markers for content made with YouTube tools or verified through provenance systems.

Axiom Math says its proofs reached peer reviewed journals

Axiom Math says proofs generated by its system have been accepted by several peer-reviewed journals, pairing machine-checkable formal proofs with human-authored papers. The development adds evidence that Artificial Intelligence tools are beginning to contribute to publishable mathematical research.

Contact Us

Got questions? Use the form to contact us.

Contact Form

Clicking next sends a verification code to your email. After verifying, you can enter your message.