Chiplet Interconnects Add Power And Signal Integrity Issues
More choices, interactions, and tiny dimensions create huge headaches.
By Adam Kovac, Semi Engineering (December 12th, 2024)
The flexibility and scalability offered by chiplets make them an increasingly attractive choice over planar SoCs, but the rollout of increasingly heterogeneous assemblies adds a variety of new challenges around the processing and movement of data.
Nearly all of the chiplets in use today were designed in-house by large systems companies and IDMs. Going forward, third-party chiplets will begin showing up in designs, as well, including some made by different foundries, and some pre-integrated with other chiplets into subsystems. This will significantly change the integration challenges, and it will require flexibility in the tools, assembly processes, and testing strategies, as well as the designs themselves.
To read the full article, click here
Related Chiplet
- DPIQ Tx PICs
- IMDD Tx PICs
- Near-Packaged Optics (NPO) Chiplet Solution
- High Performance Droplet
- Interconnect Chiplet
Related News
- Signal Integrity Plays Increasingly Critical Role In Chiplet Design
- Signal Integrity Designs at Organic Interposer CoWoS-R for HBM3-9.2Gbps High Speed Interconnection of 2.5D-IC Chiplets Integration
- Eliyan Ports Industry’s Highest Performing PHY to Samsung Foundry SF4X Process Node, Achieving up to 40 Gbps Bandwidth at Unprecedented Power Levels with UCIe-Compliant Chiplet Interconnect Technology
- Chiplets Add New Power Issues
Latest News
- CoAsia SEMI Commences Supply of 3D IC SoCs: Korea’s First Case, Positioning 3D IC as the Next HBM
- Eliyan Secures $50 Million in Strategic Investments from Leading Hyperscalers and AI Infrastructure Providers to Accelerate Scalable AI Systems
- Veeco and imec develop 300mm compatible process to enable integration of barium titanate on silicon photonics
- Lightmatter Introduces Guide Light Engine for AI, Featuring VLSP Technology
- Lightmatter and GUC Partner to Produce Co-Packaged Optics (CPO) Solutions for AI Hyperscalers