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Awesome GitHub RepositoriesQuantized Neural Network Execution
Executing deep learning operations using integer-based arithmetic with scaling factors and zero points.
Distinct from Scale and Zero-Point Calculation: Existing candidates focus on parameter calculation or specific hardware tools, not the general execution of quantized networks.
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Awesome Quantized Neural Network Execution GitHub Repositories
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- uxlfoundation/onednn
uxlfoundation/oneDNN
4,009Auf GitHub ansehenoneDNN 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
Runs integer-based deep learning operations using scaling factors and zero points to reduce memory usage and increase speed.
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