Arm has announced a number of new partnerships and integrations to improve IoT, embedded and edge AI development, including with Microsoft subsidiary Github. Development of embedded Arm applications is now integrated into Github’s automated continuous integration and delivery pipeline, which will accelerate complex IoT and embedded development. Development of automated machine learning on embedded Arm silicon also benefits from new partnerships announced with Queexo and Nota AI, which now allows the use of Arm Virtual Hardware in the cloud for automated training, with deployment to IoT environments.

The partnership announced with Github also introduces integration of Arm development tools into GitHub Actions, a continuous integration and delivery (CI/CD) platform to that allow developers to automate their build, test, and deployment pipeline. Arm says that native availability of Arm tools within Github Actions, including its cross-compiler and Arm Virtual Hardware, will allow IoT and embedded developers to improve development speed and utilisation of Arm-based silicon.

Developers can use the Arm compiler and cross-compiler natively within GitHub Actions, as well as access Arm Virtual Hardware models of Corstone-based compute systems and Arm Cortex-M processors via self-hosted and GitHub-hosted runners.

Arm Virtual Hardware was announced around a year ago and provides cloud-based virtual models of Arm subsystems and third-party development boards. It is designed to allow software developers to begin software development without using physical silicon, removing the need to build and maintain complex board farms. It allows embedded systems developers to use modern development practices such as MLOps and DevOps flows at scale. Earlier this year Arm also added models of third party development kits, widening the range of IoT applications and target environments Arm Virtual Hardware could be applied to.

The partnerships with Queexo and Nota AI bring integrations for Arm Virtual Hardware with automated machine learning (AutoML) cloud platforms. They will both be available as development targets later this year.

“We want to continue to make the advantages of Arm Virtual Hardware available wherever developers do their work, which is why we’re supporting integrations of Arm Virtual Hardware into the offerings of leading cloud-based development workflow providers,” said Paul Williamson, SVP for IoT Line of Business at Arm. We’re proud to work with these partners to empower developers to start sooner and work faster in bringing new innovations to market to address the huge opportunities in IoT. We continue to receive extremely positive feedback from our developer community, who are keen to see even more choice and support for streamlining workflows in their chosen development environments. Arm is committed to ensuring developers have the tools they need in the places they are innovating.”