Marvell Technology, Inc. has unveiled its first 2nm silicon IP, setting a new benchmark for AI and cloud infrastructure performance. Produced on TSMC’s advanced 2nm process, this breakthrough technology strengthens Marvell’s platform for developing custom XPUs, switches, and other high-performance solutions. With cloud service providers seeking greater efficiency and economic viability, Marvell’s innovation arrives at a crucial time.

Custom Silicon Drives Market Growth

As the demand for accelerated computing surges, custom silicon is projected to account for 25% of the market by 2028, with a total addressable market (TAM) growth of 45% annually. Marvell’s approach emphasizes modularity, offering a robust portfolio of semiconductor IP, including:

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  • High-speed electrical and optical serializer/deserializers (SerDes)
  • Die-to-die interconnects for 2D and 3D chip architectures
  • Advanced packaging and silicon photonics
  • Custom high-bandwidth memory (HBM) compute architecture
  • On-chip SRAM, SoC fabrics, and PCIe Gen 7 interfaces

These components enable the development of next-generation AI accelerators, CPUs, optical DSPs, and high-performance switches.

Leading the Way in Advanced Technology

Since launching the industry’s first 5nm data infrastructure silicon platform in 2020, Marvell has consistently pushed the boundaries of innovation. In 2022, the company introduced its 3nm platform, followed by the successful production of first silicon in 2023. Today, multiple standard and custom silicon products from Marvell are actively shipping and in development.

“The platform approach enables us to fast-track the development of high-speed SerDes and other essential technologies on the latest process nodes,” said Sandeep Bharathi, Chief Development Officer at Marvell. “Our long-standing collaboration with TSMC has been instrumental in delivering industry-leading performance, transistor density, and efficiency.”

Marvell’s 2nm Platform Introduces 3D Bi-Directional I/O

A major highlight of Marvell’s 2nm platform is the introduction of 3D simultaneous bi-directional I/O, operating at speeds up to 6.4 Gbps. Unlike traditional unidirectional I/O pathways, this innovation allows chip designers to double bandwidth or cut connection points by 50%, enhancing efficiency and flexibility.

As chip complexity grows, chiplet-based architectures are gaining traction. By 2028, an estimated 30% of advanced node processors will utilize chiplet designs. Marvell’s 3D simultaneous bi-directional I/O enables higher transistor density by facilitating taller die stacks, supporting the evolution toward 2.5D, 3D, and even 3.5D chip designs.

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“TSMC is honored to collaborate with Marvell on its cutting-edge 2nm platform,” said Dr. Kevin Zhang, Senior Vice President of Business Development and Global Sales, and Deputy Co-Chief Operating Officer at TSMC. “Together, we are leveraging TSMC’s industry-leading silicon and packaging technologies to drive AI-era advancements in accelerated infrastructure.”

FAQs

1. What makes Marvell’s 2nm silicon a game-changer for AI and cloud infrastructure?

Marvell’s 2nm silicon offers unparalleled efficiency, performance, and scalability, enabling faster, more cost-effective AI and cloud solutions. Its integration of high-speed SerDes, advanced packaging, and custom compute architectures ensures next-generation capabilities for cloud service providers.

2. How does Marvell’s 3D simultaneous bi-directional I/O improve chip performance?

Unlike traditional unidirectional I/O, Marvell’s 3D bi-directional I/O doubles bandwidth while reducing connection points by 50%. This innovation supports higher transistor densities and more efficient chiplet designs, essential for AI and data infrastructure.

3. What role does TSMC play in Marvell’s 2nm silicon development?

TSMC provides its cutting-edge 2nm process technology and packaging expertise to Marvell, ensuring industry-leading transistor density, power efficiency, and performance. Their collaboration accelerates the development of advanced AI and cloud computing solutions.

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