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Settings and models used to define threading and offload runtimes for target hardware environments.
Distinct from Runtime Hardware Configuration: Focuses on low-level runtime execution environment setup for compute libraries, unlike generic CLI hardware configuration.
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oneDNN is a library for deep learning acceleration that provides optimized building blocks for neural network training and inference. It manages tensor computation across CPU and GPU hardware, enabling the execution of high-performance primitives for model training and neural network inference optimization. The project distinguishes itself through hardware-specific kernel optimization and the use of just-in-time compilation to target specific processor instruction sets. It supports quantized neural network execution using both static and dynamic quantization to reduce memory usage and increas
Defines the threading model and offload runtime to match the target hardware environment.