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The Scientific Computing Resource Detector is a specialized skill designed to bridge the gap between AI development and physical hardware constraints. By automatically identifying CPU cores, GPU backends (including NVIDIA CUDA, AMD ROCm, and Apple Metal), and memory availability, it generates a structured JSON report with actionable strategic recommendations. This allows developers and AI agents to make informed architectural decisions—such as selecting between parallel processing, out-of-core computing, or GPU acceleration—before beginning resource-heavy tasks like model training or large-scale genomic analysis.
