Foundation IP: Pushing the Boundaries of Energy-Efficient Chip Design


Access “Foundation IP: Pushing the Boundaries of Energy-Efficient Chip Design” to explore six articles that explain how to address SoC design challenges using advanced Foundation IP solutions. Learn how these approaches enable energy efficiency, high performance, and reliability across key applications such as mobile, IoT, AI, HPC, automotive, crypto, and networking. Why read this digest... » read more

Delivering Automotive-Grade Quality With Customized FinFET Foundation IP


By Andrew Appleby, Daryl Seitzer, and Nafiz Ahmed The growing compute demands of modern vehicles are forcing chipmakers to venture into new territory. To deliver increased processor performance for engine and body control systems, one leading semiconductor supplier knew it had to move to an automotive-qualified FinFET technology process — a leap that would introduce significant new desi... » read more

Customizing Foundation IP For Ultra-Low-Voltage Designs


By Daryl Seitzer, Andrew Appleby, and Mohammad Tanveer Building a new system-on-chip (SoC) starts with assembling the right foundational elements—pre‑verified IP for logic, memory, I/O, and other essential functions. Standard IP solutions typically address most common design needs, but some projects call for more specialized approaches, especially when innovation is critical or when t... » read more

Power Leadership At 2nm: Foundation IP Optimized For Next-Gen Hyperscale SoCs


By Andrew Appleby and Daryl Seitzer As demand for data center compute accelerates, power efficiency has become the defining metric for modern CPUs, GPUs, and AI accelerators. Every watt saved directly impacts the massive operating costs of gigawatt-scale AI data centers, where power and cooling account for 40–60% of operational expenditures. To reduce energy consumption and strengthen t... » read more

Leveraging Foundation IP For Low-Power AI Processor Development


Artificial intelligence (AI) has become widespread in recent years, quickly establishing itself as a groundbreaking technology. AI operates on machine learning (ML) algorithms, which demand substantial computational power. Traditionally, designers have utilized graphics processing units (GPUs) to run these ML algorithms. Initially created for graphics rendering, GPUs have shown to be highly eff... » read more

Getting Optimal PPA For HPC & AI Applications With Foundation IP


By Andrew Appleby, Xiaorui Hu, and Bhavana Chaurasia The demand for application-specific system-on-chips (SoCs) for compute applications is ever-increasing. Today, the diversity of requirements means there is a need for a rich set of compute solutions in a wide range of process technologies. The resulting products may have very different but demanding power, performance, and area (PPA) requi... » read more