No title
Sparse tensor computations suffer from irregular memory access patterns that degrade cache performance. While software prefetching can mitigate this, existing compiler approaches lack the semantic insight needed for effective optimization. We present ASaP, an automatic software prefetching framework integrated within MLIR’s sparse tensor dialect. By leveraging semantic information-tensor formats a
