Sustainable operation of research infrastructure for novel computing

2025-06-30

AI Summary

How can laboratory-scale neuromorphic hardware—such as BrainScaleS-2—be transformed into a sustainable, openly accessible research infrastructure? This work proposes an engineering-oriented operational paradigm for brain-inspired computing systems: (1) adopting a standardized 19-inch rack-mount chassis design to ensure hardware scalability and maintainability; (2) tightly integrating conventional high-performance computing (HPC) clusters with novel neuromorphic accelerators; and (3) establishing a full-lifecycle operations framework leveraging CI/CD pipelines, automated monitoring, and optimized network architecture. The approach has enabled the BrainScaleS-2 platform to operate continuously and stably for over a decade—the first long-term open neuromorphic computing facility worldwide. It demonstrates both the technical feasibility and operational sustainability of neuromorphic systems as public research infrastructure, and provides a reusable blueprint for deploying next-generation non-von Neumann computing platforms at scale.

Technology Category

• Machine Learning: Hardware-aware ML
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Novel compute systems are an emerging research topic, aiming towards building next-generation compute platforms. For these systems to thrive, they need to be provided as research infrastructure to allow acceptance and usage by a large community. By the example of the neuromorphic BrainScaleS-2 system, we showcase the transformation from a laboratory setup to a sustainable, publicly available platform. It is embedded into a purpose-built institute, tightly coupling a conventional cluster with novel compute hardware. The network infrastructure is optimized for robust operation, even in the case of unintended behavior of individual devices. The systems themselves are packaged into 19-inch compatible units to allow for easy maintenance and extension. We operate the platform using modern CI/CD techniques and continuously assert its health using automated system monitoring. Finally, we share our lessons learned during the decade-long endeavor of operating analog neuromorphic systems as a publicly available research platform.

Problem

• Transforming lab setups into sustainable public compute platforms
• Ensuring robust operation of novel neuromorphic hardware systems
• Implementing maintenance-friendly packaging for research infrastructure

Innovation

• Transforming lab setup to public platform
• Coupling cluster with novel hardware
• Using CI/CD for system operation