White Papers
Downloadable White Papers
Semiconductor Value Chain with a Focus on IP Providers
By Global Semiconductor Alliance (GSA)
The semiconductor industry operates within a complex and rapidly evolving ecosystem driven by continuous innovation. Central to this ecosystem is the semiconductor value chain, which includes several key stages: chip design, wafer fabrication, final assembly, and raw material sourcing. Each stage is crucial to the production and functionality of semiconductor devices. In conjunction with the Global Semiconductor Alliance's IP Interest working group, Expedera explores how IP providers are pivotal within this framework, especially in the chip design phase.
Configurability in the Design of Integrated Chipsets
By Global Semiconductor Alliance (GSA)
The semiconductor industry is experiencing significant changes as the requirements for processing data are evolving. Computing systems must manage unparallel massive amounts of data created by users, whether machines or humans. Artificial Intelligence is the mechanism by which this data gets processed, and it is driving a rethinking of the architectures of the computing systems. In conjunction with the Global Semiconductor Alliance's IP Interest working group, Expedera explores "Configurability in the Design of Integrated Chipsets."
Impact of AI on IP and Chip Design
By Global Semiconductor Alliance (GSA)
In conjunction with the Global Semiconductor Alliance's IP Interest group, Expedera explores the impact of AI on intellectual property (IP) and Chip Design, providing comprehensive details and multifaceted data to cover all aspects of the semiconductor industry. It highlights AI growth trends, market predictions, and silicon chip design innovations. The paper also examines key sectors and their supply chains while emphasizing the critical importance of security in supporting massive AI workloads. This evolution demands a closer look at legal considerations and the need for specific skill sets that have significantly impacted labor and immigration on a global scale, which are highlighted here. The paper recommends areas where cross-industry collaboration is needed to address significant AI challenges and recommends standards that make AI in semiconductors a sustainable, scalable, and secure solution.
Transforming the Semiconductor Industry: Future Roadmap for Generative AI on the Edge
By Global Semiconductor Alliance (GSA)
In the third of a three-part series, Expedera, in conjunction with the Global Semiconductor Alliance’s Emerging Technologies (EmTech) group explores “Transforming the Semiconductor Industry: Future Roadmap for Generative AI on the Edge”. This white paper explores key applications for Generative AI and the features they enable, as well as an examination of how model growth and differing model types are driving the memory and processing roadmaps. Finally, the paper explores some of the unanswered questions related to data handling, memory, and monetization.
Unlocking Generative AI on the Edge across the Semiconductor Value Chain
By Global Semiconductor Alliance (GSA)
In the second of a three-part series, Expedera, in conjunction with the Global Semiconductor Alliance’s Emerging Technologies (EmTech) group, explores “Unlocking Generative AI on the Edge across the Semiconductor Value Chain.” Included in this white paper is an examination of how members of the value chain (including IP providers, EDA vendors, fabless chip makers, foundries, OSATs, OEMs, and service providers) can capitalize on the explosive growth of edge Generative AI.
The Impact of Generative AI on the Edge for the Semiconductor Industry
By Global Semiconductor Alliance (GSA)
In the first of a three-part series, Expedera, in conjunction with the Global Semiconductor Alliance’s Emerging Technologies (EmTech) group, explores “The Impact of Generative AI on the Edge for the Semiconductor Industry”. In this white paper, the working group explores the evolution of Generative AI (GenAI), and how can the rapidly evolving semiconductor industry can enable GenAI innovation cost-efficiently and at scale. Included in this first part is an introduction to LLMs (Large Language Models) and SLMs (Small Language Models), as well as the market dynamics around widescale adoption of Gen AI at the edge.
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.