ETTE: Efficient Tensor-Train-based Computing Engine for Deep Neural Networks
Yu Dian Gong, Miao Yin, Lingyi Huang, Jinqi Xiao, Yang Sui, Chunhua Deng, Bo Yuan · 2023
Tensor-train (TT) decomposition enables ultra-high compression ratio, making the deep neural network (DNN) accelerators based on this method very attractive. TIE, the state-of-the-art TT based DNN accelerator, achieved high performance by leveraging a compact inference scheme to remove unnecessary computations and memory access. However, TIE increases memory costs for stage-wise intermediate results and additional intra-layer data transfer, leading to limited speedups even the models are highly compressed.