…Large-scale AI models increasingly process multimodal data streams combining video, audio, and text. Efficient video compression and decompression have therefore become critical components of AI training pipelines, inference workloads, and real…
…EMIB has already been deployed in high-performance computing, AI accelerators, FPGAs, and data center products where bandwidth and power efficiency are paramount. As the number of chiplets within a package increases…
…model and Germany’s plans for defense spending supporting home-grown tech are high profile examples. Defense particularly is a compelling priority likely to override bureaucratic resistance. Another Initiative: European Chips Design…
…It supports all standard data structures, including NLDM, CCS, and LVF, ensuring that the AI-generated models are signoff-ready. Speed is not helpful if the data is flawed, and at advanced…
…Using teardown-based analysis of AI PCs including recent Microsoft Surface and ASUS Zenbook models, the report finds a consistent pattern: memory and storage, not the headline processor or NPU, account for…
…3D IC , AI , Chiplet , Events Key takeaways ▼ The 2026 Design Automation Conference ( DAC 2026 ) marks another pivotal moment for the semiconductor and electronic systems industry as artificial intelligence, chiplets, heterogeneous integration, and…
…Its flagship platform, SIM‑V, delivers industry-leading RISC‑V simulation performance and extensibility, enabling accurate modeling of complex SoCs and custom ISA extensions. The company serves diverse sectors including AI, automotive…
…how to efficiently design and verify increasingly complex AI chips. S2C, the world’s largest company focused exclusively on prototyping verification solutions, joined forces with Andes Technology, a leading provider of RISC…
…From Model Scaling to System Scaling Over the past several years, AI progress was largely driven by scaling models. In other words, expanding parameter counts, improving training methods, and unlocking new reasoning…
…Large language models require massive movement of weights, activations, and KV-cache data. As context windows expand and agentic AI systems maintain longer-running sessions, the memory footprint grows dramatically. A chip…