The Architecture of Sovereignty: Design and Implementation of a Heterogeneous Hybrid Apple Silicon-NVIDIA Cluster for Scientific Computing

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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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-13
DOI
https://doi.org/10.5281/zenodo.20684077
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

The Architecture of Sovereignty: Design and Implementation of a Heterogeneous Hybrid Apple Silicon-NVIDIA Cluster for Scientific Computing

Chun Tang
Zenodo (CERN European Organization for Nuclear Research)
Distributed and Parallel Computing Systems
article

The Architecture of Sovereignty: Design and Implementation of a Heterogeneous Hybrid Apple Silicon-NVIDIA Cluster for Scientific Computing

Chun Tang
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Karnataka State Law University (IN)
Openalex Percentile: Top 3%
Distributed and Parallel Computing Systems
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