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Found 3 papers, 1 papers with code
Reliable and Energy Efficient MLC STT-RAM Buffer for CNN Accelerators
We propose a lightweight scheme where the formation of a data block is changed in such a way that it can tolerate soft errors significantly better than the baseline.
Partition Pruning: Parallelization-Aware Pruning for Deep Neural Networks
We evaluated the performance and energy consumption of parallel inference of partitioned models, which showed a 7. 72x speed up of performance and a 2. 73x reduction in the energy used for computing pruned layers of TinyVGG16 in comparison to running the unpruned model on a single accelerator.
PyCM: Multiclass confusion matrix library in Python
PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters.
