2 papers
cs.AR2026
Rethinking LLM Inference Bottlenecks: Insights from Latent Attention and Mixture-of-Experts
Sungmin Yun, Seonyong Park, Hwayong Nam +10
Computational workloads composing traditional transformer models are starkly bifurcated. Multi-Head Attention (MHA) and Grouped-Query Attention are memory-bound due to low arithmet…
cs.CR2025
Sudoku: Decomposing DRAM Address Mapping into Component Functions
Minbok Wi, Seungmin Baek, Seonyong Park +2
Decomposing DRAM address mappings into component-level functions is critical for understanding memory behavior and enabling precise RowHammer attacks, yet existing reverse-engineer…