arXiv cs.AI
· Papers
At-the-Roofline Sparse Tensor Contractions on Vector Processors for Transformer Inference
arXiv:2607.25504v1 Announce Type: cross Abstract: Fine-grained weight pruning and activation sparsification have emerged as effective approaches for reducing the compute and memory cost of inference for Transformer models. In the moderate-sparsity regime, Gustavson's dataflow provides a natural execution model for expl