The Shift to System-Level AI Drives Next-Generation Silicon by Kalar Rajendiran on 04-27-2026 at 8:00 am View Forum Posts View Articles Private Message Categories: 3D IC , AI , Chiplet , FinFET , Foundries , TSMC Key takeaways ▼ At its 2026 Technology Symposium, TSMC delivered a clear message: the … …
… This shift toward system-level integration is essential because memory bandwidth has become one of the primary bottlenecks in AI computing. Modern AI accelerators require rapid movement of data between processors and high-bandwidth memory HBM . …
… The conference’s “Chips to Systems” branding underscores this industry shift toward holistic platform engineering. …
… Conclusion: The New Competitive Edge The New Shift-Left is about de-risking the most expensive decision in chip design: IP selection. By leveraging the speed and flexibility of FPGA prototyping early in the cycle, architects can move past theoretical models and gain hard data on system performance. …
… Arm is formalizing that shift and taking direct aim at Intel, AMD, and the internal silicon teams of hyperscalers. …
… Arm is formalizing that shift and taking direct aim at Intel and AMD. …
Why Europe Needs Its Own AI Supercomputing Platform by Daniel Nenni on 06-02-2026 at 10:00 am View Forum Posts View Articles Private Message Categories: IP , Semidynamics Key takeaways ▼ The strategic cooperation between Semidynamics and SiPearl to develop a European sovereign rack-scale AI compute… …
… With full MMU support for Linux and versatile performance scaling, AX46MPV is well suited for data center AI computation elements, Linux-capable edge AI platforms, and high-performance MPUs in storage, networking, and other performance-critical domains. “Our customers value our RISC-V IP for its pe… …
… Workloads that previously consumed hours or even days can now be completed dramatically faster through GPU acceleration and AI-assisted optimization. But the larger shift lies in how AI interacts with engineers. The industry is moving beyond generative AI into what NVIDIA described as “agentic AI”. …
… Why This Matters for AI Hardware The significance of this partnership lies in how it tackles the core constraints of modern AI workloads. As compute performance scales, the bottlenecks have shifted toward data movement, power efficiency, and system integration. …