Fine-grained assignment of approximate multipliers across layers, filters, and kernels of ResNet-8 on CIFAR-10 yields up to 54% energy savings with 4% accuracy loss.
A Survey of Techniques for Approximate Computing,
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MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators
Fine-grained assignment of approximate multipliers across layers, filters, and kernels of ResNet-8 on CIFAR-10 yields up to 54% energy savings with 4% accuracy loss.