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Semiconductor Engineering: How Cache Coherency Simplifies AI Software

How Cache Coherency Simplifies AI Software

This article explains how hardware-managed cache coherency can simplify AI software by coordinating shared data across CPUs, accelerators and chiplets. The article highlights the role of coherent and non-coherent interconnects in building scalable, efficient AI SoCs, while presenting Arteris’ Ncore, FlexNoC and FlexGen IP as complementary solutions for managing data movement.

Advancing Europe’s Automotive Innovation Ecosystem: Arteris Continues Its Work in the RIGOLETTO Project 

Advancing Europe’s Automotive Innovation Ecosystem: Arteris Continues Its Work in the RIGOLETTO Project

As software-defined vehicles reshape the automotive industry, collaborative innovation is becoming essential to developing secure, scalable computing platforms. Learn how Arteris is contributing to the European RIGOLETTO project, helping advance next-generation automotive architectures through expertise in Network-on-Chip technology, RISC-V integration, and high-performance semiconductor design.

The AI Journal: Making chiplets work for AI requires more than connectivity

Making chiplets work for AI requires more than connectivity

This article explains why building successful AI chiplet architectures requires more than high-speed die-to-die connectivity. It explores how efficient data movement, protocol selection, coherency, and intelligent NoC architecture are critical to maximizing performance, scalability, and energy efficiency in next-generation AI systems.

EDN: Model your IPs and your NoCs

Model your IPs and your NoCs

As SoC and chiplet architectures become increasingly complex, effective modeling must extend beyond functional IP blocks to include the NoC interconnect fabric itself. This article highlights why NoCs have become critical determinants of system performance and explains the value of using consistent transaction-level, cycle-accurate, and RTL models throughout the design flow.