Chiplet / Die-To-Die IP Cores

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Chiplet and die-to-die interface IP cores enable high-speed, low-latency communication between multiple dies within advanced semiconductor packages. These IP blocks are essential for modern chiplet-based architectures and heterogeneous integration.

With the growing complexity of SoC and multi-die systems, chiplet interconnect IP provides scalable solutions for integrating processors, accelerators, memory, and I/O components across multiple silicon dies.

This catalog allows you to compare chiplet and die-to-die IP cores from leading vendors based on bandwidth, latency, protocol support (UCIe, BoW, proprietary), and process and packaging compatibility.

Whether you are designing AI accelerators, data center processors, or advanced packaging solutions, you can identify the right interconnect IP for your chiplet architecture.

 
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Compare 112 Chiplet / Die-To-Die IP Cores from 26 vendors

What are chiplet and die-to-die IP cores?

Chiplet and die-to-die IP cores are specialized interconnect solutions that enable communication between multiple silicon dies داخل a single package. They are a key enabler of chiplet-based design and advanced packaging technologies.

These IP cores allow designers to partition complex systems into smaller dies, improving yield, scalability, and flexibility while maintaining high performance.

Main chiplet interconnect standards

UCIe (Universal Chiplet Interconnect Express)

UCIe is an emerging industry standard that enables interoperable die-to-die communication across chiplets from different vendors. It supports high bandwidth, low latency, and scalable system integration.

Bunch of Wires (BoW)

BoW is a simpler die-to-die interface standard designed for short-reach communication with low complexity and power consumption.

Proprietary die-to-die interfaces

Many vendors offer custom chiplet interconnect IP optimized for specific performance, power, or packaging requirements.

Key features of chiplet interconnect IP

  • High bandwidth communication between dies
  • Low latency for performance-critical applications
  • Scalability across multiple chiplets
  • Support for advanced packaging (2.5D, 3D integration)
  • Energy-efficient data transfer

How to choose a chiplet or die-to-die IP core

Selecting the right IP depends on system architecture and packaging constraints:

  • Supported standard (UCIe, BoW, or proprietary)
  • Bandwidth and latency requirements
  • Packaging technology (2.5D, 3D, interposer)
  • Power consumption and thermal considerations
  • Integration complexity and ecosystem support

Applications of chiplet and die-to-die IP

  • AI and machine learning accelerators
  • Data center processors
  • High-performance computing (HPC)
  • Networking and telecom systems
  • Advanced heterogeneous SoCs

Compare chiplet and die-to-die IP cores from leading vendors

This catalog provides access to a wide range of chiplet and die-to-die IP cores from leading semiconductor IP providers.

Use filters to compare solutions based on performance, power efficiency, standard support, and integration requirements to find the best interconnect for your chiplet architecture.

Frequently asked questions about Chiplet / Die-to-Die IP cores

What is Chiplet / Die-to-Die IP?

Chiplet / Die-to-Die IP is a reusable semiconductor IP block used in SoCs and ASICs to provide this function with faster integration, better reuse, and lower implementation risk.

What capabilities does Chiplet / Die-to-Die IP typically provide?

Die-to-die communication allows different silicon dies to exchange data efficiently, enabling modular chip design and heterogeneous integration.

Where is Chiplet / Die-to-Die IP used?

Chiplet / Die-to-Die IP is used in semiconductor designs that need this capability with proven IP, predictable integration, and faster time-to-market.

How do I choose Chiplet / Die-to-Die IP?

Chiplets improve scalability, reduce manufacturing cost, and allow designers to mix different technologies within a single package.

Why use dedicated Chiplet / Die-to-Die IP instead of building it from scratch?

They are used in AI accelerators, data center processors, HPC systems, networking chips, and advanced SoC designs.

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