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Arm’s Dipti Vachani on IoT, Edge AI and Software-Defined Vehicles

Arm’s Dipti Vachani explained how compact processors, edge AI, cloud development and SOAFEE could help address automotive computing’s power and software challenges.
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Autonomous vehicles may need data-center-scale computing, but they cannot carry a data center’s power and cooling demands. In a 2022 interview with EE Times, Arm executive Dipti Vachani described how Arm was addressing that mismatch—from compact IoT processors and cloud-based development tools to SOAFEE, an open architecture for automotive software.

Why automotive computing is a power-and-software problem

Vachani framed the challenge as more than adding processing power. A fully autonomous vehicle must handle increasingly complex software within tight limits on energy, heat and physical space. She said, “A fully autonomous vehicle will need almost a billion lines of code.” That was her 2022 estimate, not a current measurement of every autonomous vehicle’s software.

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One response, she said, was to treat the vehicle like a data center on wheels. But Vachani warned that an approach requiring extensive liquid cooling “is not going to work in a production environment.” The practical challenge is to support demanding workloads without letting computing hardware overwhelm a vehicle’s power and cooling envelope.

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How Arm connects compact processors and edge AI

M-class for small, constrained devices

Vachani pointed to Arm’s M-class processors as a fit for small, power-constrained IoT devices. In the 2022 interview, she said Arm had 215 billion devices and that “a third of those are M class.” Those are figures she attributed to Arm at the time, not independently verified current totals.

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Ethos NPUs for edge AI

For edge AI, Vachani described pairing compact processors with Ethos neural processing units (NPUs). Her point was that dedicated AI processing can reduce the memory and surrounding hardware a device needs, helping designers work within the size and power limits typical of edge systems. The interview describes the intended design benefit; it does not establish a quantified saving or a result for a particular product.

How Total Solutions and Virtual Hardware help software teams

Arm Total Solutions aims to make hardware and software co-development more consistent across systems that combine different kinds of compute, including CPUs, NPUs, image signal processors (ISPs) and GPUs. Such systems are heterogeneous: different processors handle different workloads, so teams need a development environment that helps software work across the combined platform rather than treating each component in isolation.

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Arm Virtual Hardware extends that idea into the cloud. It lets developers begin writing and testing software before the target silicon is available, potentially allowing software work to proceed earlier in a hardware project. Vachani described it as “a consistent solution environment in the cloud.” The interview presents this as a development approach, not a guarantee that cloud testing replaces validation on physical hardware.

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What SOAFEE means for software-defined vehicles

SOAFEE stands for Scalable Open Architecture for Embedded Edge. Arm describes it as an open architecture and reference implementation for applying cloud-native software practices to automotive edge systems, which must operate within safety and power constraints. The goal is to create a more common environment for developing and deploying automotive software while accounting for the realities of production vehicles.

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That work relates to the idea of the software-defined vehicle: vehicle functions can be improved or upgraded through software rather than being fixed entirely at manufacture. In an Arm podcast transcript published in 2021, Vachani defined an upgrade this way: “It’s quite simply that the function of the vehicle is upgraded, and or improved by an automatic download of software.” An over-the-air download is one mechanism for delivering an update; the broader engineering challenge is building software that can be developed, integrated and maintained across vehicle systems.

SOAFEE’s open approach also makes ecosystem participation important. A shared architecture can help align cloud-native development with embedded automotive requirements, but it is not, by itself, proof that every supplier or vehicle program uses the same tools or can move software unchanged from cloud to car.

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