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The rapid development of deep learning are enabling a plenty of novel applications such as image and speech recognition for embedded systems, robotics or smart wearable devices. However, typical deep learning models like deep convolutional neural networks (CNNs) consume so much on-chip storage and high-throughput compute resources that they cannot be easily handled by mobile or embedded devices with...
The advantages and the flexibility introduced into the hardware implementation by partial dynamic reconfiguration have rapidly changed the design flow of embedded systems. Configuration management is an important issue in operating system for dynamically reconfigurable system-on-chip. Reconfiguration overhead affects the performance of reconfigurable system. This paper presents a hardware implemented...
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