# PPoPP 2025 ## Meta Info Homepage: Paper list: ### Acceptance Rate 20.1% (= 38 / 189) ## Papers ### Large Language Models (LLMs) * LLM Training * ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training * Oregon & Pacific Northwest National Laboratory & William and Mary * Mario: Near Zero-cost Activation Checkpointing in Pipeline Parallelism * ICT, CAS * WeiPipe: Weight Pipeline Parallelism for Communication-Effective Long-Context Large Model Training * THU & NUS & CETHIK & Lynxi Technology * LLM Inference * MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models * ISTA & Universidade da Coruña & ETH & IST Austria ### Mixture-of-Experts (MoEs) * MoE Training * Harnessing Inter-GPU Shared Memory for Seamless MoE Communication-Computation Fusion * WHU & NVIDIA & UMacau ### Graph Neural Networks (GNNs) * GNN Training * Adaptive Parallel Training for Graph Neural Networks \[[Code](https://anonymous.4open.science/r/APT-1CAB)] * CUHK * GNN Inference * Helios: Efficient Distributed Dynamic Graph Sampling for Online GNN Inference * ZJU & Alibaba ### GPU Sharing * SGDRC: Software-Defined Dynamic Resource Control for Concurrent DNN Inference on NVIDIA GPUs * HKUST ### Sparse Matrix-Matrix Multiplication (SpMM) * Acc-SpMM: Accelerating General-purpose Sparse Matrix-Matrix Multiplication with GPU Tensor Cores * Computer Network Information Center, CAS & RUC & Hangzhou Dianzi University * FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores * BUPT