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ORCID29th Euro-Par 2023: Limassol, Cyprus
- José Cano
, Marios D. Dikaiakos, George A. Papadopoulos, Miquel Pericàs, Rizos Sakellariou:
Euro-Par 2023: Parallel Processing - 29th International Conference on Parallel and Distributed Computing, Limassol, Cyprus, August 28 - September 1, 2023, Proceedings. Lecture Notes in Computer Science 14100, Springer 2023, ISBN 978-3-031-39697-7
Programming, Compilers and Performance
- Karthick Panner Selvam, Mats Brorsson:
DIPPM: A Deep Learning Inference Performance Predictive Model Using Graph Neural Networks. 3-16 - Juan Pedro Gutiérrez H. Muriedas, Katharina Flügel, Charlotte Debus, Holger Obermaier, Achim Streit, Markus Götz:
perun: Benchmarking Energy Consumption of High-Performance Computing Applications. 17-31 - Aaron Welch, Oscar R. Hernandez, Stephen W. Poole:
Extending OpenSHMEM with Aggregation Support for Improved Message Rate Performance. 32-46 - Roberto Rocco, Gianluca Palermo:
Fault-Aware Group-Collective Communication Creation and Repair in MPI. 47-61
Scheduling, Resource Management, Cloud, Edge Computing, and Workflows
- Yi Yang, Xiang Li, Yeting Xu, Wenzhong Li, Jiangyi Hu, Taishan Xu, Xiancheng Ren, Sanglu Lu:
MetaLive: Meta-Reinforcement Learning Based Collective Bitrate Adaptation for Multi-Party Live Streaming. 65-80 - Anne Benoit, Louis-Claude Canon, Redouane Elghazi, Pierre-Cyrille Héam:
Asymptotic Performance and Energy Consumption of SLACK. 81-95 - Tomasz Kanas, Krzysztof Rzadca:
A Poisson-Based Approximation Algorithm for Stochastic Bin Packing of Bernoulli Items. 96-110 - Francesc Lordan, Gabriel Puigdemunt, Pere Vergés, Javier Conejero, Jorge Ejarque, Rosa M. Badia:
Hierarchical Management of Extreme-Scale Task-Based Applications. 111-124 - Kurt Horvath, Dragi Kimovski, Christoph Uran, Helmut Wöllik, Radu Prodan:
MESDD: A Distributed Geofence-Based Discovery Method for the Computing Continuum. 125-138 - Istenç Tarhan, Jacques Carlier, Claire Hanen, Antoine Jouglet, Alix Munier Kordon:
Parameterized Analysis of a Dynamic Programming Algorithm for a Parallel Machine Scheduling Problem. 139-153 - Moysis Symeonides, Demetris Trihinas, George Pallis, Marios D. Dikaiakos:
SparkEdgeEmu: An Emulation Framework for Edge-Enabled Apache Spark Deployments. 154-168 - Pirah Noor Soomro, Nikela Papadopoulou, Miquel Pericàs:
ODIN: Overcoming Dynamic Interference in iNference Pipelines. 169-183 - Manaswini Piduguralla, Saheli Chakraborty, Parwat Singh Anjana, Sathya Peri:
DAG-Based Efficient Parallel Scheduler for Blockchains: Hyperledger Sawtooth as a Case Study. 184-198 - Feng Li, Fengguang Song:
INSTANT: A Runtime Framework to Orchestrate In-Situ Workflows. 199-213 - Jonas H. Müller Korndörfer, Ahmed Eleliemy, Osman Seckin Simsek, Thomas Ilsche, Robert Schöne, Florina M. Ciorba:
How Do OS and Application Schedulers Interact? An Investigation with Multithreaded Applications. 214-228 - Louis-Claude Canon, Damien Landré, Laurent Philippe, Jean-Marc Pierson, Paul Renaud-Goud:
Assessing Power Needs to Run a Workload with Quality of Service on Green Datacenters. 229-242
Architectures and Accelerators
- Zhihua Fan, Wenming Li, Shengzhong Tang, Xuejun An, Xiaochun Ye, Dongrui Fan:
Improving Utilization of Dataflow Architectures Through Software and Hardware Co-Design. 245-259 - Hongbing Tan, Jing Zhang, Libo Huang, Xiaowei He, Dezun Dong, Yongwen Wang, Liquan Xiao:
A Multi-level Parallel Integer/Floating-Point Arithmetic Architecture for Deep Learning Instructions. 260-274 - Wenhai Li, Zhiling Cheng, Yuan Chen, Ao Li, Lingfeng Deng:
Lock-Free Bucketized Cuckoo Hashing. 275-288 - Zhaoteng Meng, Long Xiao, Xiaoyao Gao, Zhan Li, Lin Shu, Jie Hao:
BitHist: A Precision-Scalable Sparse-Awareness DNN Accelerator Based on Bit Slices Products Histogram. 289-303 - Shiju Li, Kevin Tang, Jin Lim, Chul-Ho Lee, Jongryool Kim:
Computational Storage for an Energy-Efficient Deep Neural Network Training System. 304-319
Data Analytics, AI, and Computational Science
- Bo Zhang, Philip E. Davis, Nicolas M. Morales, Zhao Zhang, Keita Teranishi, Manish Parashar:
Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA. 323-338 - Chao Peng, Yiming Guo, Yao Chen, Qilin Rui, Zhengfeng Yang, Chenyang Xu:
FedGM: Heterogeneous Federated Learning via Generative Learning and Mutual Distillation. 339-351 - Xiaoyun Zhang, Yaohua Wang, Dezun Dong, Cunlu Li, Shaocong Wang, Liquan Xiao:
DeTAR: A Decision Tree-Based Adaptive Routing in Networks-on-Chip. 352-366 - Hongyu Chen, Zhejiang Ran, Keshi Ge, Zhiquan Lai, Jingfei Jiang, Dongsheng Li:
Auto-Divide GNN: Accelerating GNN Training with Subgraph Division. 367-382 - Gianluca Mittone, Walter Riviera, Iacopo Colonnelli, Robert Birke, Marco Aldinucci:
Model-Agnostic Federated Learning. 383-396 - Fernando Vázquez-Novoa, Javier Conejero, Cristian Tatu, Rosa M. Badia:
Scalable Random Forest with Data-Parallel Computing. 397-410 - Daniel Hofstätter, Shashikant Ilager, Ivan Lujic, Ivona Brandic:
SymED: Adaptive and Online Symbolic Representation of Data on the Edge. 411-425 - Xiaofeng Hou, Jiacheng Liu, Xuehan Tang, Chao Li, Kwang-Ting Cheng, Li Li, Minyi Guo:
MMExit: Enabling Fast and Efficient Multi-modal DNN Inference with Adaptive Network Exits. 426-440
Theory and Algorithms
- Peter Sanders, Daniel Seemaier:
Distributed Deep Multilevel Graph Partitioning. 443-457 - Zhen Xie, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath:
TrainBF: High-Performance DNN Training Engine Using BFloat16 on AI Accelerators. 458-473 - Enrico Dandolo, Andrea Pietracaprina, Geppino Pucci:
Distributed k-Means with Outliers in General Metrics. 474-488 - Anastasios Zouzias, William F. McColl:
A Parallel Scan Algorithm in the Tensor Core Unit Model. 489-502 - Kilian Grage, Klaus Jansen, Felix Ohnesorge:
Improved Algorithms for Monotone Moldable Job Scheduling Using Compression and Convolution. 503-517 - Dominik Bojko, Marek Klonowski, Mateusz Marciniak, Piotr Syga:
On Size Hiding Protocols in Beeping Model. 518-532 - Dominik Bojko, Marek Klonowski, Dariusz R. Kowalski, Mateusz Marciniak:
Efficient Protective Jamming in 2D SINR Networks. 533-546
Multidisciplinary, Domain-Specific and Applied Parallel and Distributed Computing
- Tiago Trevisan Jost, Arun Thangamani, Raphaël Colin, Vincent Loechner, Stéphane Genaud, Bérenger Bramas:
GPU Code Generation of Cardiac Electrophysiology Simulation with MLIR. 549-563 - Ziyu Zhang, Junshi Chen, Zhanming Wang, Yifan Luo, Jineng Yao, Shenghong Huang, Hong An:
SWSPH: A Massively Parallel SPH Implementation for Hundred-Billion-Particle Simulation on New Sunway Supercomputer. 564-577 - Benoît Martin, Laurent Prosperi, Marc Shapiro:
Transactional-Turn Causal Consistency. 578-591 - Shuai Lu, Jun Chu, Luanzheng Guo, Xu T. Liu:
Im2win: An Efficient Convolution Paradigm on GPU. 592-607 - Gabin Schieffer, Ivy Bo Peng:
Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores. 608-622 - Zekai Chen, Fuyi Wang, Shengxing Yu, Ximeng Liu, Zhiwei Zheng:
FedCML: Federated Clustering Mutual Learning with non-IID Data. 623-636 - Jasmin Mohnke, Michael Wagner:
A Look at Performance and Scalability of the GPU Accelerated Sparse Linear System Solver Spliss. 637-648 - Abdul Qadir Ibrahim, Sebastian Götschel, Daniel Ruprecht:
Parareal with a Physics-Informed Neural Network as Coarse Propagator. 649-663 - Robin Kobus, Johannes Nelgen, Valentin Henkys, Bertil Schmidt:
Faster Segmented Sort on GPUs. 664-678 - Javier García Blas, Genaro Sanchez-Gallegos, Cosmin Petre, Alberto Riccardo Martinelli, Marco Aldinucci, Jesús Carretero:
Hercules: Scalable and Network Portable In-Memory Ad-Hoc File System for Data-Centric and High-Performance Applications. 679-693 - Seyed Saberi, Günther Meschke, Andreas Vogel:
An Efficient Parallel Adaptive GMG Solver for Large-Scale Stokes Problems. 694-709 - Andreas Irmler, Raghavendra Kanakagiri, Sebastian T. Ohlmann, Edgar Solomonik, Andreas Grüneis:
Optimizing Distributed Tensor Contractions Using Node-Aware Processor Grids. 710-724 - Felix Liu, Albin Fredriksson, Stefano Markidis:
Parallel Cholesky Factorization for Banded Matrices Using OpenMP Tasks. 725-739
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