Computing for All: Hot Aisle + Red Hat (Neural Magic) + AMD

Hot Aisle is teaming up with Red Hat’s Neural Magic and AMD to accelerate the future of open AI infrastructure. This collaboration showcases how high-performance inference on AMD MI300x hardware, powered by vLLM and sparse model optimization, can thrive outside of proprietary hyperscaler stacks. By providing bare-metal access and real-world benchmarking support, Hot Aisle enables faster iteration, deeper optimization, and meaningful upstream contributions, all in service of decentralizing and democratizing compute for developers, enterprises, and the broader open-source community.

May 15, 2025

Computing for All: Hot Aisle + Red Hat (Neural Magic) + AMD

AI infrastructure is at a crossroads. The rapid acceleration of model size, complexity, and usage is outpacing the accessibility of the compute required to support it. Meanwhile, the traditional pathways to scalable performance, namely hyperscalers and proprietary stacks, remain expensive, opaque, and often exclusionary. At Hot Aisle, we believe there’s a better way forward: open hardware, open software, and infrastructure built on decentralization, not gatekeeping.
That’s why we’re excited to publicly share our collaboration with Neural Magic, now part of Red Hat, and AMD, focused on pushing the performance boundaries of open inference frameworks like vLLM on AMD’s MI300x platform.
Neural Magic brings deep expertise in sparse model optimization and software-defined compute. Their engineering team has already made massive contributions to the vLLM ecosystem, and with Red Hat now in the picture, their work is positioned to scale across the enterprise Linux ecosystem. This is a powerful combination: open model inference, running on open hardware, delivered through an open platform.
Red Hat (Neural Magic) uses Hot Aisle’s bare-metal MI300x cluster as part of their ongoing development and benchmarking workflow. We provide the performance headroom and direct ROCm access they need to unlock new optimizations, whether that’s kernel tuning, memory layout experimentation, or workload profiling across real-world inference loads. This kind of iteration isn’t possible inside a virtualized hyperscaler sandbox, and it’s certainly not easy to do with hardware access that’s shared, throttled, or abstracted away. The result: faster development cycles, better performance, and tangible upstream contributions to the AMD and vLLM ecosystem.
Why does this matter?
Because the ability to run models efficiently on non-NVIDIA hardware is now a strategic priority, not just for infrastructure providers, but for the health of the AI ecosystem itself. Developers need choice. Enterprises need viable alternatives. Open-source communities need pathways to contribute and validate. Without this, we risk re-centralizing the most important compute layer of the 21st century into a single stack, controlled by a handful of vendors.
The collaboration between Red Hat (Neural Magic) and AMD, backed by infrastructure from Hot Aisle, is a real-world demonstration that the decentralization and democratization of compute is possible. It’s a validation of the thesis that high-performance compute can be commoditized, that innovation can come from decentralized actors, and that hardware and software co-design doesn’t have to be locked behind closed doors.
At Hot Aisle, we built our platform for exactly this kind of work. We believe the future of AI infrastructure is built on top of bare metal, not managed services. We believe developers should be able to access top-tier compute without long term contracts. And we believe that meaningful progress happens when companies like Red Hat (Neural Magic) are free to explore, iterate, and ship improvements that benefit everyone.
This partnership is more than just technical collaboration, it’s a signal. It shows that the stack is shifting, that AMD’s hardware strategy is gaining traction, and that Red Hat (Neural Magic) is serious about pushing open inference frameworks forward. We’re honored to support that work with infrastructure that matches the ambition.
The road to democratizing compute isn’t easy, but it’s real, and it’s happening right now. And we’re just getting started.
 
 
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