The Neuromorphic Commons
THOR is the US hub for open-access large-scale neuromorphic research.
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Jan 20, 2025
The nature article examines the current state of neuromorphic technology and provides a roadmap for building the next generation of scalable systems. The authors emphasize that as the energy consumption of traditional AI doubles, neuromorphic computing offers a promising, energy-efficient solution. The paper highlights the critical need for an open ecosystem, collaborative research, and user-friendly software to lower the barrier to entry and accelerate the field's growth.
August 22, 2025
This collaborative effort brought together representatives from SpiNNcloud, UT Systems and THOR to install the cutting-edge system, which consists of 56 individual boards. The successful deployment of this infrastructure provides a powerful, on-site resource that is foundational to the THOR project's mission of advancing large-scale neuromorphic computing research.
October 21-23, 2025
This collaborative effort brought together representatives from SpiNNcloud, UT Systems and THOR to install the cutting-edge system, which consists of 56 individual boards. The successful deployment of this infrastructure provides a powerful, on-site resource that is foundational to the THOR project's mission of advancing large-scale neuromorphic computing research.
We envision a future where interdisciplinary collaboration on biological intelligence is seamless. Through close partnerships with industry, THOR will empower researchers to request, co-develop, deploy, and evaluate neuromorphic experiments on heterogeneous computing hardware systems. This platform will enable a richer understanding of computational models, algorithms, neuromorphic hardware, and real-world applications that benefit from bio-inspired processing.
Deployed at the University of Texas at San Antonio, THOR's infrastructure is hosted and maintained on-site. This provides a stable and reliable resource, ensuring community researchers have the ability to innovate and push the boundaries of what's possible in neuromorphic computing.
