CMU-SAFARI / sasiml

An extensible and fully programable cycle-accurate Spatial Architecture simulator for Machine Learning Workloads. Described in detail in the IEEE TC 2023 paper by Orosa et al. at https://arxiv.org/abs/2202.02310

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