Extending network-on-chip (NoC) technology to chiplets
By Frank Schirrmeister, Arteris
EDN (November 15, 2023)
A monolithic integrated circuit (IC) is one in which everything is implemented on a single silicon die, also called a chip. The maximum practical size for a die using extreme ultraviolet (EUV) lithographic process is around 25 mm x 25 mm = 625 mm2. Although it’s possible to build larger dice, their yields start to fall off rapidly. So, one solution for today’s multi-billion transistor devices is to disaggregate the design into multiple smaller dice mounted on a silicon interposer, presented in a single package. In this case, the smaller dice are referred to as chiplets or tiles, while the final device is known as a multi-die system.
There are multiple advantages associated with adopting a chiplet-based approach. These include increased yield, reduced die cost, and the ability to implement different functions on optimal process technologies. Also, there are increased flexibility and customization options because designers can pick and choose the appropriate chiplets for different applications. This method delivers increased scalability because more chiplets can address higher workload demands and reduced time to market by reusing existing chiplets in various combinations across different products.
To read the full article, click here
Related Chiplet
- Integrated voltage regulator (IVR) chiplet
- High-performance connectivity chiplets
- eFPGA Chiplet
- DPIQ Tx PICs
- IMDD Tx PICs
Related Technical Papers
- NoCs and the transition to multi-die systems using chiplets
- Challenges and Opportunities to Enable Large-Scale Computing via Heterogeneous Chiplets
- An Introduction to Direct RF Sampling in a World Evolving Towards Chiplets – Part 1
- Advanced Packaging and Chiplets Can Be for Everyone
Latest Technical Papers
- ThAME: 3D Memory-Enabled Heterogeneous Accelerator for LLM Mixture of Experts
- Thermo-mechanical reliability evaluation and comparative fatigue assessment of 2.5D chiplet packages with viscoelastic C4 underfill
- AI-Driven Thermal Mapping and Management in 3D Integrated Photonic Circuits
- CLIP-3D: Closed-Loop Evaluation of Performance and Physical Constraints for 3D ICs
- StreamDQ: Near-Memory Weight DeQuantization in Custom HBM for Scalable AI Inference Acceleration