TSMC and Synopsys Collaborate to Introduce NVIDIA’s Revolutionary Computational Lithography into Manufacturing

NVIDIA, TSMC, and Synopsys collaborate to utilize NVIDIA's computational lithography platform, aiming to advance semiconductor chip manufacturing and explore new frontiers in scaling.

NVIDIA's collaboration with TSMC and Synopsys will push the boundaries of physics and accelerate the production of next-generation chips.
The use of accelerated computing and generative AI in computational lithography significantly improves the semiconductor manufacturing process, reducing costs, space, and power consumption.
The partnership between NVIDIA, TSMC, and Synopsys enables angstrom-level scaling and reduces turnaround time by orders of magnitude through the power of accelerated computing.

nVidia has made a significant announcement today, revealing that TSMC and Synopsys will be utilizing NVIDIA’s computational lithography platform to advance semiconductor chip manufacturing. This collaboration aims to push the boundaries of physics and accelerate the production of next-generation chips.

Jensen Huang, the founder and CEO of NVIDIA, emphasized the importance of computational lithography in chip manufacturing. He stated that their partnership with TSMC and Synopsys leverages accelerated computing and generative AI to explore new frontiers in semiconductor scaling.

In addition to this collaboration, NVIDIA has introduced new generative AI algorithms that enhance cuLitho, a library for GPU-accelerated computational lithography. These algorithms significantly improve the semiconductor manufacturing process, surpassing current CPU-based methods.

The computational lithography workload is known to be highly demanding, consuming billions of hours on CPUs annually. For instance, creating a mask set for a chip can require over 30 million hours of CPU compute time. To address this, NVIDIA’s accelerated computing allows 350 NVIDIA H100 systems to replace 40,000 CPU systems. This not only accelerates production time but also reduces costs, space, and power consumption.

TSMC CEO Dr. C.C. Wei expressed his satisfaction with the integration of GPU-accelerated computing in their workflow. This collaboration has resulted in remarkable performance improvements, including enhanced throughput, reduced cycle time, and lower power requirements. Moving forward, TSMC plans to leverage NVIDIA cuLitho in their production processes to drive critical components of semiconductor scaling.

Since its introduction last year, cuLitho has enabled TSMC to explore new opportunities for innovative patterning technologies. In joint testing with shared workflows, TSMC and NVIDIA achieved a 45x speedup for curvilinear flows and nearly 60x improvement for more traditional Manhattan-style flows. These flows differ in terms of mask shapes, with curvilinear flows allowing for curved mask shapes, while Manhattan flows restrict mask shapes to horizontal or vertical orientations.

Synopsys, a leader in delivering advanced techniques for accelerating computational lithography, also expressed their excitement about the collaboration. Their Proteus optical proximity correction software, when running on the NVIDIA cuLitho software library, significantly speeds up computational workloads compared to current CPU-based methods. This partnership with TSMC and NVIDIA plays a crucial role in enabling angstrom-level scaling and reducing turnaround time by orders of magnitude through the power of accelerated computing.

Furthermore, NVIDIA has developed generative AI algorithms to further enhance the cuLitho platform. This new workflow provides an additional 2x speedup on top of the already accelerated processes enabled by cuLitho. By applying generative AI, NVIDIA enables the creation of a near-perfect inverse mask to account for light diffraction. The final mask is then derived using traditional and physically rigorous methods, resulting in a two-fold acceleration of the overall optical proximity correction (OPC) process.

The fab process often requires revisions in OPC due to various changes, leading to increased compute requirements and bottlenecks in the fab development cycle. However, the combined power of cuLitho’s accelerated computing and generative AI alleviates these costs and bottlenecks. This allows fabs to allocate available compute capacity and engineering bandwidth to develop novel solutions for new technologies beyond the 2 nm node.

Overall, NVIDIA’s collaboration with TSMC and Synopsys marks a significant milestone in advancing semiconductor chip manufacturing. By leveraging accelerated computing and generative AI, this partnership opens up new possibilities for scaling and optimization in the industry.

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Background Information

About nVidia:

NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

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About Synopsys:

Synopsys is a important American software company that specializes in electronic design automation (EDA) and semiconductor intellectual property. Founded in 1986, Synopsys provides tools and solutions for designing and testing complex integrated circuits and electronic systems. Their software aids in the development of semiconductors, electronic products, and software applications, playing a crucial role in advancing technological innovation across various industries. For more detailed information about their products and contributions, you can visit their official website at

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About TSMC:

TSMC, or Taiwan Semiconductor Manufacturing Company, is a semiconductor foundry based in Taiwan. Established in 1987, TSMC is a important player in the global semiconductor industry, specializing in the manufacturing of semiconductor wafers for a wide range of clients, including technology companies and chip designers. The company is known for its semiconductor fabrication processes and plays a critical role in advancing semiconductor technology worldwide.

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Technology Explained

CPU: The Central Processing Unit (CPU) is the brain of a computer, responsible for executing instructions and performing calculations. It is the most important component of a computer system, as it is responsible for controlling all other components. CPUs are used in a wide range of applications, from desktop computers to mobile devices, gaming consoles, and even supercomputers. CPUs are used to process data, execute instructions, and control the flow of information within a computer system. They are also used to control the input and output of data, as well as to store and retrieve data from memory. CPUs are essential for the functioning of any computer system, and their applications in the computer industry are vast.

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GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.