
The author introduces Tensor Homomorphic Compression (THC) as a novel bi-directional compression framework to address communication overhead in distributed deep learning. THC enables direct aggregation of compressed values, eliminating computational overhead and improving training efficiency.


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accelerating-distributed-deep-learning-using-tensor-homomorphic-compression


Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression


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Tensor Homomorphic Compression (THC) accelerates distributed deep learning by eliminating computational overheads and improving accuracy.


thc-accelerating-distributed-deep-learning-using-tensor-homomorphic-compression


THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression



THC introduces a novel bi-directional compression framework to accelerate distributed deep learning by eliminating computational overheads and improving accuracy.


tensor-homomorphic-compression-thc-for-accelerating-distributed-deep-learning


Tensor Homomorphic Compression (THC) for Accelerating Distributed Deep Learning
