Evaluation of Optimized CNNs on Heterogeneous Accelerators Using a Novel Benchmarking Approach

Numerous algorithmic optimization techniques have been proposed to alleviate the computational complexity of convolutional neural networks. Given the broad selection of AI accelerators, it is not obvious which approach benefits from which optimization most. The design space includes a large number of deployment settings (batch sizes, power modes, etc.) and unclear measurement methods. This researc...