White Papers
Downloadable White Papers
Trends in Intellectual Property
By Global Semiconductor Alliance (GSA)
Intellectual Property (IP) is a crucial aspect of the semiconductor industry. It refers to the legal rights that protect the creations of the mind, such as inventions, literary and artistic works, designs, and symbols used in commerce. In the semiconductor industry, IP is used to protect the value created by companies that invest massive amounts of money in research and development.
Security in AI
By Global Semiconductor Alliance (GSA)
Protecting AI with robust security measures is not an option but a necessity in the age of AI. Organizations must take proactive approaches in identifying and mitigating security risks to ensure the integrity, reliability, and proper use of AI systems. By implementing the strategies and considerations outlined in this document, semiconductor companies can enhance their AI security posture, protect their assets, and maintain trust in AI-driven solutions to best protect internal, customer, partner, and vendor assets.
An Ideal Architecture for Always-on Camera Subsystems
Always-sensing camera implementations offer a wealth of user experience advantages but face significant power, latency, and privacy concerns if not done right. In a joint white paper with Rambus, Expedera discusses An Ideal Architecture for Always-on Camera Subsystems.
Heterogeneous Integration - Chiplets
Chiplets are a hot topic in the semiconductor industry, and to many, represent a paradigm change for chip designers and chip consumers alike. While heterogenous chiplets seem to have multiple advantages over traditional monolithic silicon and even homogenous chiplets, they still have not been mass-market deployed. This white paper, published in cooperation with the Global Semiconductor Alliance, explores the commercial, interface, packaging, and security issues heterogenous chiplets face, along with recommendations for the industry’s successful deployment of heterogenous chiplets.
Architectural Considerations for Compute-in-Memory in AI Inference
Can Compute-in-Memory (CIM) bring new benefits to AI (Artificial Intelligence) inference? CIM is not an AI solution; rather, it is a memory management solution. CIM could bring advantages to AI processing by speeding up the multiplication operation at the heart of AI model execution.
The Road Ahead for SoCs in Self-Driving Vehicles
Automakers have relied on a human driver behind the wheel for more than a century. With Level 3 systems in place, the road ahead leads to full autonomy and Level 5 self-driving. However, it’s going to be a long climb. Much of the technology that got the industry to Level 3 will not scale in all the needed dimensions—performance, memory usage, interconnect, chip area, and power consumption.
Expedera Redefines AI Acceleration for the Edge
By Linley Gwennap, Principal Analyst, The Linley Group
Expedera is a small company with big ideas. Rather than optimizing the usual AI techniques, the company rethought neural-network acceleration from the ground up, creating a unique approach that greatly improves performance while maintaining consistent power and die area.