Project Open Se Cura Open Source Announcement

(Source: Google Open Source Blog)

As AI permeates our lives, developing secure, scalable, and efficient compute systems is crucial for safe and trustworthy AI experiences. However, hardware advancements lag behind machine learning (ML) models and software development, hindering the deployment of secure and efficient full-stack systems. Furthermore, consumer demand for smaller devices outpaces battery technology advancements, constraining the power envelope and limiting the capabilities of deployable AI systems.

Towards these challenges, Google is launching Project Open Se Cura, an open-source framework to accelerate the development of secure, scalable, transparent and efficient AI systems. Previously known internally as Project Sparrow, Project Open Se Cura is a testament to our commitment to open-source development. Our goal with Open Se Cura is to evolve a set of open-source design tools and IP libraries that will accelerate the development of full-stack systems with ML workloads through co-design and development. This will enable us to better center system designs around security, efficiency, and scalability, empowering the next generation of AI experiences.

This work was developed in close collaboration with our partners such as lowRISC, Antmicro and VeriSilicon for key parts of the tooling and infrastructure. lowRISC has contributed a transparent root of trust, along with development and integration tools, ensuring a secure foundation for the project. Antmicro has contributed system simulation tooling with Renode and expertise in open-source system-level software. VeriSilicon has contributed expertise in IP design, silicon design, BSP development and commercialization. And together, we’ve used these tools for the first time to extend our IP library with secure ML capabilities and generated a proof of concept for a low-power AI system.

To accelerate open development and transparency of AI system design, we’re releasing our entire code base for developers to consider -- you can get started by following the instructions in the README.md.

Going forward, we’ll continue to evolve Open Se Cura in the open and seek to onboard additional partners, such as Cambridge University (for CHERI innovations) and the University of Michigan (for low-power and generative AI). We are excited to explore what we can build with these new tools and hope the open source community will join us and contribute.

We look forward to working with the open-source community to drive new innovations and new AI experiences with secure, scalable and efficient ML systems.

By Kai Yick – Research Cerebra Open Source team