PipeSC: a split computing framework for pipeline implementations considering independent input batch sizes
Split computing has gained attention in deep learning as a scheme for edge computing. Split computing splits a model into head and tail models. The head model is executed on the local device and its output sent to the edge server. This output forms the input to the tail model that resides on the edg...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/181324 |