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4 months agoAccelerating Neural Networks: The Power of Quantization | HackerNoon
Neural networks are becoming larger and more complex, but their applications increasingly require running on resource-constrained devices such as smartphones, wearables, microcontrollers, and edge devices. Quantization enables: - Reducing model size: For example, switching from float32 to int8 can shrink a model by up to 4 times. - Faster inference: Integer arithmetic is faster and more energy-efficient. - Lower memory and bandwidth requirements: This is critical for edge/IoT devices and embedded scenarios.
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