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ORCID30th Euro-Par 2024: Madrid, Spain - Part II
- Jesús Carretero
, Sameer Shende, Javier García-Blas, Ivona Brandic, Katzalin Olcoz, Martin Schreiber:
Euro-Par 2024: Parallel Processing - 30th European Conference on Parallel and Distributed Processing, Madrid, Spain, August 26-30, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14802, Springer 2024, ISBN 978-3-031-69765-4
Architectures and Accelerators
- Yunkun Liao, Jingya Wu, Wenyan Lu, Xiaowei Li, Guihai Yan:
Efficient RNIC Cache Side-Channel Attack Detection Through DPU-Driven Architecture. 3-17 - Jonas Hahnfeld, Jakob Blomer, Thorsten Kollegger:
Parallel Writing of Nested Data in Columnar Formats. 18-31 - Xingbin Wang, Dan Meng, Rui Hou, Yan Wang:
FakeGuard: Novel Architecture Support for Deepfake Detection Networks. 32-46 - Stepan Nassyr, Dirk Pleiter:
Exploring Processor Micro-architectures Optimised for BLAS3 Micro-kernels. 47-61 - Dario Muñoz-Muñoz, Félix García Carballeira, Diego Camarmas-Alonso, Alejandro Calderón Mateos, Jesús Carretero:
Fault Tolerant in the Expand Ad-Hoc Parallel File System. 62-76 - Hongbing Tan, Xiaowei He, Guichu Sun, Liquan Xiao, Yuanhu Cheng, Jing Zhang, Zhong Zheng, Quan Deng, Bingcai Sui, Yongwen Wang, Libo Huang:
ImSPU: Implicit Sharing of Computation Resources Between Vector and Scalar Processing Units. 77-90 - Dengke Han, Meng Wu, Runzhen Xue, Mingyu Yan, Xiaochun Ye, Dongrui Fan:
ADE-HGNN: Accelerating HGNNs Through Attention Disparity Exploitation. 91-106 - Xuan Zhang, Zhuoran Song, Xing Li, Zhezhi He, Naifeng Jing, Li Jiang, Xiaoyao Liang:
Watt: A Write-Optimized RRAM-Based Accelerator for Attention. 107-120 - Marius Meyer, Tobias Kenter, Lucian Petrica, Kenneth O'Brien, Michaela Blott, Christian Plessl:
Optimizing Communication for Latency Sensitive HPC Applications on up to 48 FPGAs Using ACCL. 121-136 - Chuhui Wang, Zewen Ye, Haibin Shen, Kejie Huang:
A Folded Computation-in-Memory Accelerator for Fast Polynomial Multiplication in BIKE. 137-151 - Hamidreza Ramezani-Kebrya, Matei Ripeanu:
(re)Assessing PiM Effectiveness for Sequence Alignment. 152-166 - Leandro Fiorin, Cristina Silvano:
MEPAD: A Memory-Efficient Parallelized Direct Convolution Algorithm for Deep Neural Networks. 167-181 - Keegan Sanchez, Alex Gavin, Suren Byna, Kesheng Wu, Xuechen Zhang:
A High-Performance Collective I/O Framework Leveraging Node-Local Persistent Memory. 182-195 - Mohammad Hafezan, Reza Jahadi, Ehsan Atoofian:
PCTC: Hardware and Software Co-design for Pruned Capsule Networks on Tensor Cores. 196-210 - Pedro H. C. Rigon, Brenda S. Schussler, Alexandre Sardinha, Pedro M. Silva, Fábio Oliveira, Alexandre Carissimi, Jairo Panetta, Filippo Spiga, Arthur Francisco Lorenzon, Philippe O. A. Navaux:
Harnessing Data Movement Strategies to Optimize Performance-Energy Efficiency of Oil & Gas Simulations in HPC. 211-225 - Steef Hegeman, Daan Wöltgens, Anton Wijs, Alfons Laarman:
Compact Parallel Hash Tables on the GPU. 226-241 - Gabriel Gomez-Lopez, Miguel Sánchez de la Rosa, Jesús Escudero-Sahuquillo, Pedro Javier García, Francisco J. Quiles, Pierre-Axel Lagadec:
Hybrid Congestion Control for BXI-Based Interconnection Networks. 242-256
Data Analytics, AI and Computational Science
- Yunkun Liao, Hanyue Lin, Jingya Wu, Wenyan Lu, Huawei Li, Xiaowei Li, Guihai Yan:
Athena: Add More Intelligence to RMT-Based Network Data Plane with Low-Bit Quantization. 259-273 - Zhi Lu, Songfeng Lu, Yongquan Cui, Junjun Wu, Hewang Nie, Jue Xiao, Zepu Yi:
Lightweight Byzantine-Robust and Privacy-Preserving Federated Learning. 274-287 - Guangyao Zhou, Haocheng Lan, Yuanlun Xie, Wenhong Tian, Jiahong Qian, Teng Su:
CSIMD: Cross-Search Algorithm with Improved Multi-dimensional Dichotomy for Micro-Batch-Based Pipeline Parallel Training in DNN. 288-301 - Yuxiang Zhang, Xin Liu, Meng Wu, Wei Yan, Mingyu Yan, Xiaochun Ye, Dongrui Fan:
Disttack: Graph Adversarial Attacks Toward Distributed GNN Training. 302-316 - Krishna Teja Chitty-Venkata, Varuni Katti Sastry, Murali Emani, Venkatram Vishwanath, Sanjif Shanmugavelu, Sylvia Howland:
WActiGrad: Structured Pruning for Efficient Finetuning and Inference of Large Language Models on AI Accelerators. 317-331 - Hewang Nie, Songfeng Lu, Mu Wang, Jue Xiao, Zhi Lu, Zepu Yi:
VeriChroma: Ownership Verification for Federated Models via RGB Filters. 332-345 - Haoran Dang, Meng Wu, Mingyu Yan, Xiaochun Ye, Dongrui Fan:
GDL-GNN: Applying GPU Dataloading of Large Datasets for Graph Neural Network Inference. 346-361 - Thorsten Wittkopp, Philipp Wiesner, Odej Kao:
LogRCA: Log-Based Root Cause Analysis for Distributed Services. 362-376 - Héctor Martínez, Francisco D. Igual, Rafael Rodríguez-Sánchez, Sandra Catalán, Adrián Castelló, Enrique S. Quintana-Ortí:
Inference with Transformer Encoders on ARM and RISC-V Multicore Processors. 377-392 - Jiguang Lv, Shuchun Xu, Xiaodong Zhan, Tao Liu, Dapeng Man, Wu Yang:
FedGG: Leveraging Generative Adversarial Networks and Gradient Smoothing for Privacy Protection in Federated Learning. 393-407 - Yuhang Li, Tong Liu, Wenfeng Shen, Yangguang Cui, Weijia Lu:
Improving Generalization and Personalization in Long-Tailed Federated Learning via Classifier Retraining. 408-423 - Weigang Zhang, Biyu Zhou, Xing Wu, Chaochen Gao, Zhibing Liu, Xuehai Tang, Ruixuan Li, Jizhong Han, Songlin Hu:
Quartet: A Holistic Hybrid Parallel Framework for Training Large Language Models. 424-438 - Kohei Hiraga, Osamu Tatebe:
PEANUTS: A Persistent Memory-Based Network Unilateral Transfer System for Enhanced MPI-IO Data Transfer. 439-453 - Mengde Zhu, Wanyi Ning, Qi Qi, Jingyu Wang, Zirui Zhuang, Haifeng Sun, Jun Huang, Jianxin Liao:
FLUK: Protecting Federated Learning Against Malicious Clients for Internet of Vehicles. 454-469 - Pranjal Naman, Yogesh Simmhan:
Optimizing Federated Learning Using Remote Embeddings for Graph Neural Networks. 470-484 - Lin Wang, Yuchong Hu, Yuxue Liu, Renzhi Xiao, Dan Feng:
Asymmetric Coded Distributed Computation for Resilient Prediction Serving Systems. 485-499
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