DiffAxE uses conditional diffusion models to generate hardware accelerator designs directly from target performance, achieving orders-of-magnitude faster design space exploration with lower error than existing optimization methods.
Chen et al., ``Eyeriss: An energy-efficient reconfigurable accelerator for deep convolutional neural networks,'' in IEEE International Solid-State Circuits Conference (ISSCC)
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DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration
DiffAxE uses conditional diffusion models to generate hardware accelerator designs directly from target performance, achieving orders-of-magnitude faster design space exploration with lower error than existing optimization methods.