Products for Computational Storage

Arm is the world's leading technology provider of silicon IP for the intelligent system-on-chips at the heart of billions of devices. Our portfolio of products enable partners to innovate and get-to-market faster on a secure architecture built for performance and power efficiency. Find the right processor IP for your application.

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Supreme performance at optimal power
Powering the most energy-efficient embedded devices
Robust real-time performance
Custom-designed for ultimate performance and specific market needs
Highest performance for machine learning inference
Highest graphics performance for flagship gaming experiences
Higher graphics performance combined with power efficiency
Advanced ISPs for human display and computer vision applications
Scalable and flexible for cloud to edge infrastructure
Fully verified, PPA-optimized, customizable Neoverse compute subsystems
Powerful solutions for physical security applications
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Cortex-R

Cortex-R82

Highest performance real-time processor.
  • Offers efficient, high-performance compute for complex storage applications.
  • Supports Arm Neon technology for ML acceleration.
  • Implements MMU for rich OS support.
A Comprehensive Guide to Understand AI Inference on the CPU thumbnail

Understanding AI Inference on Arm CPUs

Demand for running AI workloads on CPU is growing. This comprehensive guide provides a deep dive into CPU inference and the use cases for which this may be the practical choice. Explore the industries that are already benefiting from AI on CPU and learn about real-world examples.

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Arm’s cutting-edge solutions are easily accessible through our subscription-based licensing options. In just a few clicks, find out if your company has an active subscription to the technology that’s shaping the future of computing.

Once you confirm your subscription, explore a treasure trove of IP, powerful tools, and innovative models—all designed to help elevate your projects and get you started on building the future of computing on Arm.

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