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Found 2 papers, 1 papers with code
Intel nGraph: An Intermediate Representation, Compiler, and Executor for Deep Learning
The current approach, which we call "direct optimization", requires deep changes within each framework to improve the training performance for each hardware backend (CPUs, GPUs, FPGAs, ASICs) and requires $\mathcal{O}(fp)$ effort; where $f$ is the number of frameworks and $p$ is the number of platforms.
An Artificial Neural Networks based Temperature Prediction Framework for Network-on-Chip based Multicore Platform
This thermal profile of the chip is then used by the predictive DTM that combines both core level and network level DTM techniques.
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