A multi-objective Bayesian optimization framework co-optimizes CIM crossbar hardware and DNN parameters for VGG8/CIFAR-10 and VGG16/Tiny-ImageNet, achieving comparable accuracy with up to 65% smaller area and 52% lower energy.
Gandse: Gen- erative adversarial network-based design space exploration for neural network accelerator design
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Bayesian Optimization of Crossbar-Based Compute-In-Memory System Design for Efficient DNN Inference
A multi-objective Bayesian optimization framework co-optimizes CIM crossbar hardware and DNN parameters for VGG8/CIFAR-10 and VGG16/Tiny-ImageNet, achieving comparable accuracy with up to 65% smaller area and 52% lower energy.