…By replacing proprietary networks and complementing existing standards, UALink provides the efficient, scalable backbone needed for next-gen AI systems. Ultra Ethernet: Scaling Out AI Across the Data Center As AI models…
…Today the market is primarily investing in AI chips which must execute AI models with explosive complexity growth. It is not a surprise that emulation architectures with a performance advantage for executing…
…A photo is taken, processed, and done. The NPU fires, does its work, and goes quiet. That’s efficient for visual computing. It is the wrong model for a Colin-class AI…
…The data issue is more challenging than AI model training, where scaling laws gave us a clear improvement trajectory. But to get high quality and accuracy customers need to understand, clean and…
…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…
…In an on-stage appearance alongside Intel CEO Lip-Bu Tan, Synopsys CEO Sassine Ghazi reached into his pocket, pulled out a chip, and held it up for the audience. That chip…
…As AI infrastructure, chiplets, 2.5D and 3D integration, advanced packaging, firmware adaptation, and fleet-scale operation continue to converge, the integrity of the evidence loop becomes as important as the integrity…
…Synopsys and TSMC Unite to Power the Future of AI and Multi-Die Innovation AI Everywhere in the Chip Lifecycle: Synopsys at AI Infra Summit 2025 Synopsys Collaborates with TSMC to Enable…
The explosive growth of large language models (LLMs) has created substantial new requirements for chip-to-chip interconnects. These very large models are trained in high-performance data centers. Multiple accelerators need…
…They needed to validate their chip design against real MIPI-based image sensors and cameras. However, in a virtual emulation environment, this was impossible because virtual models can mimic protocol behavior but…