Total Compute Provides Scalable Solutions for Mobile Computing
As mobile computing expands into every aspect of our lives, Arm-based smartphones, laptops, wearables, and other smart devices are everywhere. The number of compute-intensive use cases for these devices is rising every year, performing tasks we could only dream of in the past.
Arm offers a broad range of IP, software, and tools to support these advanced compute requirements. Moving to a focused solution built on a Total Compute strategy enables increased chip performance and efficiency in a smaller area. This also enables developers, semiconductor companies and OEMs to respond quickly to increased demand for innovative digital immersion experiences on mobile devices.
Sparking the Potential of Mobile Computing
Total Compute Solutions Powering the Next Decade of Mobile Computing
A solution-focused approach that spans across Arm technology components including hardware IP, physical IP, software, tools and standards.
Click the hotspots to learn more about the elements that make up a Total Compute Solution, from processors to the software ecosystem.
Components of a Total Compute Solution
Designed for complex compute tasks, such as hosting a rich operating system platform and supporting multiple software applications.
Provides the ultimate user experience for entertainment and visual applications across a wide range of smartphone devices.
Delivers the highest throughput and efficiency in the lowest area for machine learning inference for mobile computing devices.
Enables system designers to configure and build high-performance, power-efficient SoCs.
Cortex-X Custom Program
A partner program that focuses on ultimate performance. Through close collaboration with lead partners, Arm enables ultimate performance on devices.
The Basis for a Solution Approach
Arm’s Total Compute Strategy
Total Compute is the evolution from a product focus to use-case driven solutions. It adopts a holistic system approach that ensures compute platforms can seamlessly and securely handle the workloads of tomorrow—even with the proliferation of more devices, use cases and killer apps that require powerful compute resources.

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