SpiNNcloud Systems today announced that its cutting-edge supercomputing platform, built on the SpiNNaker2 architecture, has been adopted by the Neuromorphic Commons (THOR), marking a major milestone in the advancement of brain-inspired high-performance computing (HPC) and artificial intelligence (AI).
SAN FRANCISCO, CA / ACCESS Newswire / November 12, 2025 / The SpiNNaker2-based system now ranks among the top four largest neuromorphic computing platforms globally, simulating over 393 million neurons. Designed by Professor Steve Furber, the original architect of ARM, SpiNNaker2 leverages a massively parallel array of low-power processors to deliver scalable, energy-efficient performance for both AI and neuroscience workloads.
THOR is a first-of-its-kind U.S. initiative funded by the National Science Foundation (NSF) to democratize access to large-scale, heterogeneous neuromorphic computing infrastructure. By integrating SpiNNcloud’s technology, THOR provides researchers with unprecedented access to a full-stack neuromorphic ecosystem, accelerating innovation in sustainable AI, brain-inspired algorithms, and next-generation computing paradigms.
THOR is led by Dr. Dhireesha Kudithipudi, the Robert F. McDermott Chair in Engineering at the University of Texas at San Antonio (UTSA) and Director of the university’s MATRIX AI Consortium. The SpiNNaker2 system will be housed at The UT San Antonio (UTSA).
“UT San Antonio is proud to be the first U.S. academic institution to adopt SpiNNaker2 technology,” said Dr. Kudithipudi. Widely recognized for her pioneering work in energy-efficient computing and as the lead of the THOR project, she added, “Brain-inspired architectures like SpiNNcloud’s open new algorithmic pathways with a much smaller energy footprint-a balance that is critical to sustainable AI.”
The SpiNNcloud system integration will be led by Dr. Tej Pandit. Co-investigators of THOR are Dr. Catherine Schuman and Dr. Gert Cauwenberghs. Dr. Vijay Janapa Reddi will support benchmarking efforts.
“The SpiNNcloud’s system at UT San Antonio aligns with our goals to explore sparse neural networks and energy-efficient AI computing” – Dr. Vijay Janapa Reddi, Harvard University, and co-founder of MLCommons.
The installation at UT San Antonio underscores the growing demand for alternative supercomputing architectures as organizations seek scalable, sustainable computing resources for advancing discovery across AI and HPC.
“The deployment to the THOR consortium is a testament to the growing demand for energy-efficient, massively parallel, brain-inspired architectures and their critical role in shaping the future of AI” said Dr. Hector Gonzalez, CEO of SpiNNcloud. Customers leverage SpiNNcloud’s brain-inspired systems for AI-driven drug discovery, hybrid AI models, and at-scale HPC, from physics simulations to large-scale optimization powering a broad spectrum of AI and HPC use cases, while SpiNNcloud pioneers a novel architecture for sparse LLMs and generative-AI inference, delivering radical efficiency gains.
About SpiNNcloud
SpiNNcloud is redefining AI infrastructure with its brain-inspired architecture, built to deliver unprecedented computational and energy efficiency. Its event-driven architecture mirrors how the brain processes information, computing only what matters, when it matters, unlocking unprecedented efficiency without compromising performance. SpiNNcloud delivers complete systems to customers advancing AI and high-performance computing, providing a fundamentally different path that is scalable, sustainable, and engineered for the future of intelligent computing.
Use for media free of charge. Picture credits: © Tej Pandit, UT San Antonio
Press contact
Dr. Maurice Chales de Beaulieu, SpiNNcloud Systems GmbH
Phone: +49 351 21776005, [email protected]
SOURCE: SpiNNcloud Systems GmbH
