Vendor: Arm Ltd. Category: Edge AI Accelerator

Highly Scalable and Efficient Second-Generation ML Inference Processor

Arm’s second-generation, scalable and efficient NPU, the Ethos-N78 enables new immersive applications with a 2.5x increase in sin…

Overview

Arm’s second-generation, highly scalable and efficient NPU, the Ethos-N78 enables new immersive applications with a 2.5x increase in single-core performance now scalable from 1 to 10 TOP/s and beyond through many-core technologies. It provides flexibility to optimize the ML capability with 90+ configurations.

Key features

  • Increased Performance
    • Improves user experience with 2.5x increased single-core performance scalable from 1 to 10 TOP/s and beyond through many-core technologies.
  • Improved Efficiency
    • Up to 40 percent lower DRAM bandwidth (MB/Infr) and up to 25 percent increase in efficiency (inf/s/mm2) enables demanding neural networks to be run in diverse solutions.
  • Extended Configurability
    • Target multiple markets with the flexibility to optimize ML capabilities with 90+ configurations and the Ethos-N Static Performance Analyzer.
  • Unified Software and Tools
    • Develop, deploy, and debug with the Arm AI platform using online or offline compilation and Arm Development Studio 5 Streamline.

Specifications

Identity

Part Number
ETHOS-N78
Vendor
Arm Ltd.
Type
Silicon IP

Files

Note: some files may require an NDA depending on provider policy.

Provider

HQ: Great Britain

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What is Highly Scalable and Efficient Second-Generation ML Inference Processor?

Highly Scalable and Efficient Second-Generation ML Inference Processor is a Edge AI Accelerator IP core from Arm Ltd. listed on Semi IP Hub.

How should engineers evaluate this Edge AI Accelerator?

Engineers should review the overview, key features, supported foundries and nodes, maturity, deliverables, and provider information before shortlisting this Edge AI Accelerator IP.

Can this semiconductor IP be compared with similar products?

Yes. Buyers can compare this product with similar semiconductor IP cores or IP families based on category, provider, process options, and structured technical specifications.

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