Sparse matrix multiplications—including SpMV, SpMM, and SpGEMM—are fundamental to scientific computing, graph analytics, and machine learning. Despite extensive GPU-focused optimizations such as custom sparse formats and load balance, CSR-style and block-based methods can still underexploit fine-grained cache locality...
Xing Cong, Fu-Kai Sun, Yi-Ding Liu et al.· 0 citations
DB-SpMSpV is presented, a dual-view blocked SpMSpV framework for dynamic GPU workloads that uses load balancing, asynchronous prefetching, and hierarchical writeback to reduce irregular memory accesses, writeback conflicts, and load imbalance and is integrated into DB-BFS and DB-Decoding.
Xing Cong, Chen-Hao Xie, Rui Wang et al.· Proceedings of the Internati...· 0 citations
R2Act, a recovery-action evaluation framework for post-diagnosis incident response, provides a reproducible, simplified starting point for research and evaluation and reveals that many recovery failures arise not from missing diagnostic knowledge, but from the difficulty of translating diagnostic evidence into valid re...
