MaxQ: Multi-Axis Query for N:M Sparsity Network

arXiv:2312.07061v2 Announce Type: replace
Abstract: N:M sparsity has received increasing attention due to its remarkable performance and latency trade-off compared with structured and unstructured sparsity. However, existing N:M sparsity methods do not differentiate the relative importance of weights among blocks and leave important weights underappreciated. Besides, they directly apply N:M sparsity to the whole network, which will cause severe information loss. Thus, they are still sub-optimal. In this paper, we propose an efficient and effective Multi-Axis Query methodology, dubbed as …

arxiv cs.cv network query sparsity type