This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications.
The exponential growth in computational power is slowing at a time when the amount of compute consumed by state-of-the-art deep learning (DL) workloads is rapidly growing.
Model size, serving latency, and power constraints are a significant challenge in the deployment of DL models for many applications.
| Systems | The algorithms compilers and processor components to efficiently train and deploy deep learning models for commercial applications |
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Morgan & Claypool Deep learning systems: algorithms, compilers, and processors for large-scale production, paperback/andres rodriguez
