For decades, high-performance CPU design has been dominated by traditional out-of-order (OOO) execution architectures. Giants like Intel, Arm, and AMD have refined this approach into an industry standard—balancing performance and complexity through increasingly sophisticated schedulers, speculation, and runtime … Read More
Artificial Intelligence
eBook on Mastering AI Chip Complexity: Pathways to First-Pass Silicon Success
The rapid evolution of artificial intelligence (AI) is transforming industries, from autonomous vehicles to data centers, demanding unprecedented computational power and efficiency. As highlighted in Synopsys’ guide, the global AI chip market is projected to reach $383 billion by 2032, growing at a 38% CAGR. This … Read More
Synopsys Enables AI Advances with UALink
The evolution of hyperscale data center infrastructure to support the processing of trillions of parameters for large language models has created some rather substantial design challenges. These massive processing facilities must scale to hundreds of thousands of accelerators with highly efficient and fast connections.… Read More
A Big Step Forward to Limit AI Power Demand
By now everyone knows that AI has become the all-consuming driver in tech and that NVIDIA GPU-based platforms are the dominant enabler of this revolution. Datacenters worldwide are stuffed with such GPUs, serving AI workloads from automatically drafting emails and summarizing meetings to auto-creating software and controlling… Read More
Perforce Webinar: Can You Trust GenAI for Your Next Chip Design?
GenAI is certainly changing the world. Every day there are new innovations in the use of highly trained models to do things that seemed impossible just a short while ago. As GenAI models take on more tasks that used to be the work of humans, there is always a nagging concern about accuracy and bias. Was the data used to train the model … Read More
A Principled AI Path to Spec-Driven Verification
I have seen a flood of verification announcements around directly reading product specs through LLM methods, and from there directly generating test plans and test suite content to drive verification. Conceptually automating this step makes a lot of sense. Carefully interpreting such specs even today is a largely manual task,… Read More
448G: Ready or not, here it comes!
The march toward higher-speed networking continues to be guided by the same core objectives as has always been : increase data rates, lower latency, improve reliability, reduce power consumption, and maintain or extend reach while controlling cost. For the next generation of high-speed interconnects, these requirements … Read More
PDF Solutions and the Value of Fearless Creativity
PDF Solutions has been around for over 30 years. The company began with a focus on chip manufacturing and yield. Since the beginning, PDF Solutions anticipated many shifts in the semiconductor industry and has expanded its impact with enhanced data analytics and AI. Today, the company’s impact is felt from design to manufacturing,… Read More
Gartner Top Strategic Technology Trends for 2025: Agentic AI
Agentic AI refers to goal-driven software entities—“digital coworkers”—that can plan, decide, and act on an organization’s behalf with minimal supervision. Unlike classic chatbots or coding assistants that respond only to prompts, agentic systems combine models (e.g., LLMs) with memory, planning, tools/APIs, sensing,… Read More
A Quick Tour Through Prompt Engineering as it Might Apply to Debug
The immediate appeal of large language models (LLMs) is that you can ask any question using natural language in the same way you would ask an expert, and it will provide an answer. Unfortunately, that answer may be useful only in simple cases. When posing a question we often implicitly assume significant context and skate over ambiguities.… Read More
Rapidus, IBM, and the Billion-Dollar Silicon Sovereignty Bet