Overview
System-on-chip designs are proliferating to help OEMs automate functions such as smart lights, heating and cooling, wireless door locks, smoke, fire, and intrusion detection and more. SoC designers building chips for these applications need a feature rich 32-bit computing platform that provides a roadmap to enhanced functionality over time. The AndesCore™ N8 with its 3-stage pipeline design boosts the execution efficiency of today's computation algorithms, reduces memory usage, lowers customers' silicon cost, while providing a long-term roadmap for customers needing an upgrade path from 8-bit cores.
Motion, magnetic, pressure, light and temperature sensors are at the heart of IoT devices for home automation. Embedded processors to control these sensors and communicate their readings to the web must be power efficient enough to run on batteries sometimes last more than 10 years, for example the intrusion sensors on door and windows. The N8 achieves 1.82 DMIPS/MHz, which are far more computing power and energy conservation than its peers.
Learn more about CPU IP core
本月,头部数字EDA企业思尔芯宣布,荣获RISC-V处理器IP领导厂商Andes晶心科技(Andes Technology)颁发的“2026年度最佳合作伙伴”奖项。该荣誉旨在表彰思尔芯在RISC-V生态共建、原型验证平台支撑及联合市场拓展中与Andes晶心深度协同、持续创造客户价值的突出表现。
This award recognizes Quintauris’ exceptional dedication to develop reference architectures and advancing mass-market commercialization for the RISC-V ecosystem with Andes.
Based on Visual Studio Code (VS Code), it is integrated, lightweight, and designed to streamline the development experience by bringing Andes’ industry-leading toolchain and advanced debugging capabilities directly into the most popular integrated development environment (IDE).
Built upon the production-proven D23 architecture, the 32-bit D23-SE processor is specifically engineered for safety-critical systems requiring deterministic performance, robust security mechanisms, and accelerated SoC compliance workflow.
This milestone release addresses one of the industry’s most challenging hurdles: enabling resource-heavy Transformer architectures such as Vision Transformers (ViT), Vision-Language Models (VLMs), and Small Language Models (SLMs) to execute efficiently on power- and cost-constrained edge platforms.
Validated Architecture Models Enable Early Design Exploration and Pre-RTL Optimization