Products for Telecom
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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Cortex-A
Cortex-A710
- Addition of Armv9 architecture features for enhanced performance and security.
- Optimal for mobile compute use cases such as smartphones and smart TVs.
- 30% increase in energy efficiency compared to Cortex-A78.
Cortex-A520
- Most performant, high-efficiency CPU with improved power efficiency (up to 22% vs Cortex-A510) for DoU/real-world use cases.
- New QARMA3 PAC algorithm lowers the performance cost, strengthening PAC deployment in the consumer technology market.
- AArch64-only CPU for building big.LITTLE clusters across the consumer technology market.
Cortex-A510
- Large performance increases for a highly efficient CPU.
- Innovative microarchitecture upgrades.
- Over 3x uplift in ML performance compared to Cortex-A55.
Cortex-A78
- Built for next generation consumer devices.
- Enabling immersive experiences on new form factors and foldables.
- Improving ML device responsiveness and capabilities such as face and speech recognition.
Cortex-A78C
- Performance for laptop class productivity and gaming on-the-go.
- Advanced data and device security with Pointer Authentication.
- Improved scalability with up to 8 big core only configuration and up to 8MB L3 cache.
Cortex-A77
- Leadership performance and efficiency for 5G mobile solutions.
- Improved responsiveness for on device machine learning.
- Built for next-gen smartphones and laptops.
Cortex-A76
- Designed for devices undertaking complex compute tasks.
- Greater single threaded performance and improved energy efficiency.
- Enables faster responsiveness and at-the-edge support for machine learning applications.
Cortex-A75
- Flexible architecture provides a broad ecosystem of support.
- Executes up to three instructions in parallel per clock cycle.
- Broad market use covers smartphones, servers, automotive applications and more.
Cortex-A73
- Increased power efficiency of up to 30 percent over predecessors.
- Smallest Armv8-A processor.
- Designed for mobile and consumer applications.
Cortex-A72
- Advanced branch predictor reduces wasted energy consumption.
- Gain significant advantages in reduced memory requirements.
- Suitable for implementation in an Arm big.LITTLE configuration.
Cortex-A55
- Flexible design meets requirements to support broad market application.
- Ideal for smaller devices with constrained environments.
- Designed for compatibilty with DynamIQ configurations.
Cortex-A53
- Available in Arm Flexible Access.
- The choice for high single thread and FPU/Neon performance.
- Supports a wide range of applications across automotive and networking and more.
- Most widely deployed 64-bit Armv8-A processor.
Cortex-R
Cortex-R5
- Dual core configurations enables twice the performance of previous Cortex-R processors.
- Ideally suited for the development of safety-critical products.
- Most commonly used in high-volume deeply embedded SoC applications.
Neoverse
Neoverse N3
- 20% greater performance-per-watt efficiency compared to Neoverse N2.
- 2MB L2 cache option offers nearly 3x performance gains on ML workloads.
Neoverse Compute Subsystems
Neoverse CSS N3
- Highly configurable to target 5G, enterprise networking, and infrastructure edge use cases.
- Supports from 8 to 32 Neoverse N3 cores per die.
Neoverse CSS N2
- Up to 64 Neoverse N2 cores in a 5nm advanced process.
- Up to 1MB L2 private cache per core and up to 64MB shared system-level cache.
- Up to 8x DDR5 40b or LPDDR5 channels.
- Up to 4x x16 PCIe/CXL Gen5 lanes.
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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