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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,
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Semiconductor Engineering: Avoid The Hidden Bottleneck Of Integration At Scale
This Semiconductor Engineering article examines how SoC integration has become a major bottleneck as designs scale in complexity, with growing numbers of IP blocks, registers, and hardware/software interfaces.
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The AI Journal: 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
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Semiconductor Engineering: Reducing Avoidable Memory Trips In HBM Systems
As AI and high-performance SoCs increasingly rely on HBM, memory bandwidth alone is no longer enough to maximize performance. This article discusses why the intelligent data movement and cache efficiency are critical to unlocking the full benefits of HBM-based architectures.
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Beyond Moore’s Law: Heterogeneous Computing and AI SoCs
As Moore’s Law slows, heterogeneous computing is driving AI, automotive, and data center innovation through specialized compute, chiplets, and advanced interconnects.
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Achieving ASIL Compliance in Automotive AI Systems 
Learn how automotive companies are approaching ASIL compliance for AI systems using safety islands, redundancy, and functional safety architectures.
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Semiconductor Engineering: Using SystemC TLM Modeling To Solve AI Data Movement Challenges
SystemC TLM modeling helps AI chip architects analyze NoC data movement early, identify bandwidth and latency bottlenecks, optimize workload behavior, and reduce RTL-stage performance and integration risk. Learn more about how early NoC modeling improves AI system design and accelerates
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EDN: How data movement defines performance for AI silicon
This article explores how AI chip performance is increasingly constrained by data movement rather than raw compute power, highlighting the growing role of network-on-chip (NoC) architectures, chiplets, cache hierarchies, and physically aware design in modern AI SoCs. Learn more about
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Design & Reuse: A Repeatable Framework for Hardware Security Assurance
This article explores how hardware security assurance is evolving into a structured, repeatable process for evaluating third-party IP in increasingly complex SoC and RISC-V designs.
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Semiconductor Engineering: Facilitating Complex SoC Design Through Automation And Integration
Automation and integration tools unify IP, connectivity, and software design, enabling scalable, efficient SoC development and reducing manual complexity. Learn more about how unified system definitions, automated interconnect generation, and coordinated design flows improve performance, productivity, and time-to-market in the
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