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ORCID31st Euro-Par 2025: Dresden, Germany - Part II
- Wolfgang E. Nagel, Diana Goehringer
, Pedro C. Diniz:
Euro-Par 2025: Parallel Processing - 31st European Conference on Parallel and Distributed Processing, Dresden, Germany, August 25-29, 2025, Proceedings, Part II. Lecture Notes in Computer Science 15901, Springer 2026, ISBN 978-3-031-99856-0
Architectures and Accelerators
- Jiangying Xue, Tianyu Xiong, Lingwei Chao, Ruini Xue:
SimPoint+: More Stable, Accurate and Efficient Program Analysis. 3-17 - Yi Luo, Yaobin Wang, Qi Wang, Yingchen Song, Huan Wu, Qingfeng Wang, Jun Huang:
DCI: An Efficient Workload-Aware Dual-Cache Allocation GNN Inference Acceleration System. 18-32 - Ruimin Shi, Gabin Schieffer, Maya B. Gokhale, Pei-Hung Lin, Hiren D. Patel, Ivy Peng:
ARM SVE Unleashed: Performance and Insights Across HPC Applications on Nvidia Grace. 33-47 - Joonyup Kwon, Jinhyeok Choi, Ngoc-Son Pham, Sangwon Shin, Taeweon Suh:
SkipNZ: Non-zero Value Skipping for Efficient CNN Acceleration. 48-59 - Jiale Dong, Hao Wu, Zihao Wang, Wenqi Lou, Zhendong Zheng, Lei Gong, Chao Wang, Xuehai Zhou:
CoQMoE: Co-Designed Quantization and Computation Orchestration for Mixture-of-Experts Vision Transformer on FPGA. 60-74 - Yudong Mu, Zhihua Fan, Xiaoxia Yao, Wenming Li, Zhiyuan Zhang, Honglie Wang, Xuejun An, Xiaochun Ye:
FDHA: Fusion-Driven Heterogeneous Accelerator for Efficient Diffusion Model Inference. 75-88 - Zhenxuan Xiong, Libo Huang, Ling Yang, Hui Guo, Junhui Wang, Zhong Zheng, Songwen Pei, Gang Chen, Yongwen Wang:
SONet: Towards Practical Online Neural Network for Enhancing Hard-to-Predict Branches. 89-102 - Piyumal Ranawaka, Per Stenström:
BATCH-DNN: Adaptive and Dynamic Batching for Multi-DNN Accelerators. 103-117 - Mengyue Xi, Jingyi He, Xianwei Zhang:
CacheC: LLM-Based GPU Cache Management to Enhance Kernel Concurrency. 118-131 - Hao Lan, Ziang Zhou, Qi Zhu, Wei Yan, Qinfen Hao, Xiaochun Ye, Yong Liu, Ninghui Sun:
ParTEE: A Framework for Secure Parallel Computing of RISC-V Trusted Execution Environments. 132-145 - Jin Pu, Shengan Zheng, Penghao Sun, Guifeng Wang, Xin Xie, Linpeng Huang:
CSGC: Collaborative File System Garbage Collection with Computational Storage. 146-160 - Zhaoyang Zeng, Yujuan Tan, Jiali Li, Zhuoxin Bai, Jun Liu, Kan Zhong, Duo Liu, Ao Ren:
Cocache: An Accurate and Low-Overhead Dynamic Caching Method for GNNs. 161-174 - Kazi Asifuzzaman, Aaron R. Young, Prasanna Date, Shruti R. Kulkarni, Narasinga Rao Miniskar, Matthew J. Marinella, Jeffrey S. Vetter:
ReSpike: A Co-Design Framework for Evaluating SNNs on ReRAM-Based Neuromorphic Processors. 175-189
Data analytics, AI, and Computational Science
- Xuanzheng Wang, Shuo Miao, Zihan Zhu, Peng Qu, Youhui Zhang:
AlphaSparseTensor: Discovering Faster Sparse Matrix Multiplication Algorithms on GPUs for LLM Inference. 193-206 - Zhichen Feng, Xin Zhang:
DiffNO: Neural Operator Learning Using Physically Structured Constrained Diffusion Model. 207-220 - Xinjue Zheng, Zhangqiang Ming, Yuchong Hu, Chenxuan Yao, Wenxiang Zhou, Rui Wang, Xun Chen, Dan Feng:
Saving Memory via Residual Reduction for DNN Training with Compressed Communication. 221-235 - Jacob Garby, Philippas Tsigas:
Interval-Asynchrony: Delimited Intervals of Localised Asynchrony for Fast Parallel SGD. 236-249 - Matyás Brabec, Jirí Klepl, Michal Töpfer, Martin Krulis:
Tutoring LLM into a Better CUDA Optimizer. 250-263 - Rubayet Rahman Rongon, Xuechen Zhang:
iAug: Accelerating Augmentation with Importance Sampling in Deep Neural Network Training. 264-277 - Nicolás Hernández, Pedro A. Toledo, Vicente Blanco, Francisco Almeida:
2:4 Pruning on Edge Devices: Performance, Energy Efficiency and Accuracy. 278-291 - Ao Chen, Guangli Li, Feng Yu, Xueying Wang, Jiacheng Zhao, Huimin Cui, Xiaobing Feng, Jingling Xue:
TopServe: Task-Operator Co-scheduling for Efficient Multi-DNN Inference Serving on GPUs. 292-305 - Sanjif Shanmugavelu, Mathieu Taillefumier, Christopher Culver, Vijay Ganesh, Oscar R. Hernandez, Ada Sedova:
Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability. 306-320 - Loris Belcastro, Paolo Ferragina, Giovanni Manzini, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio:
Scalable Compression of Massive Data Collections on HPC Systems. 321-334 - Tianyu Guo, Hande Dong, Yichong Leng, Feng Liu, Cheater Lin, Nong Xiao, Xianwei Zhang:
EFIM: Efficient Serving of LLMs for Infilling Tasks with Improved KV Cache Reuse. 335-348 - Cheng Gu, Gang Li, Xuan Zhang, Jiayao Ling, Xiaolong Lin, Zhuoran Song, Jian Cheng, Xiaoyao Liang:
Light-DiT: An Importance-Aware Dynamic Compression Framework for Diffusion Transformers. 349-364 - Sabtain Ahmad, Thomas Schneidergruber, Ivona Brandic, Johannes Scholz:
On-Device Federated Learning for Remote Alpine Livestock Monitoring. 365-379
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