Study showcases a novel computing cluster that reduces costs for scientific computing, suggesting improved accessibility.
We present the design, implementation, and benchmarking of the "God-Stack"—a standalone, heterogeneous computing cluster aimed at addressing the crisis of rising costs and declining accessibility in scientific computing by strategically integrating Apple Silicon and NVIDIA CUDA architectures into a system orchestrated via Ray. The cluster offers over 768 GB of unified memory and 102 CPU cores, featuring a custom "Sovereign-Dispatch" task routing layer designed to optimize task allocation based on workload characteristics. This paper documents two validation case studies demonstrating the system's ability to independently tackle computational challenges previously considered intractable, all at a fraction of the cost of traditional cloud solutions.
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Chun Tang (2026) studied this question.
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