| 2023 | A Dynamic Network-Native MPI Partitioned Aggregation Over InfiniBand Verbs. Yiltan Hassan Temuçin, Scott Levy, Whit Schonbein, Ryan E. Grant, Ahmad Afsahi |
| 2023 | A Finite-Difference Time-Domain (FDTD) solver with linearly scalable performance in an FPGA cluster. Zhenyu Xu, Miaoxiang Yu, Jillian Cai, Qing Yang, Tao Wei |
| 2023 | A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression. Arkaprabha Ganguli, Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello |
| 2023 | Accelerating Distributed ML Training via Selective Synchronization. Sahil Tyagi, Martin Swany |
| 2023 | Communication-Avoiding Recursive Aggregation. Yihao Sun, Sidharth Kumar, Thomas Gilray, Kristopher K. Micinski |
| 2023 | DEHype: Retrofitting Hypervisors for a Resource-Disaggregated Environment. Taehoon Kim, Kwangwon Koh, Changdae Kim, Eunji Pak, Yeonjeong Jeong, Sang-Hoon Kim |
| 2023 | DoW-KV: A DPU-offloaded and Write-optimized Key-Value Store on Disaggregated Persistent Memory. Yiwen Zhang, Guokuan Li, Jiguang Wan, Junyue Wang, Jun Li, Ting Yao, Huatao Wu, Daohui Wang |
| 2023 | Efficient Intra-Rack Resource Disaggregation for HPC Using Co-Packaged DWDM Photonics. George Michelogiannakis, Yehia Arafa, Brandon Cook, Liang Yuan Dai, Abdel-Hameed A. Badawy, Madeleine Glick, Yuyang Wang, Keren Bergman, John Shalf |
| 2023 | Exact Distributed Stochastic Block Partitioning. Frank Wanye, Vitaliy Gleyzer, Edward K. Kao, Wu-chun Feng |
| 2023 | ExplSched: Maximizing Deep Learning Cluster Efficiency for Exploratory Jobs. Hongliang Li, Hairui Zhao, Zhewen Xu, Xiang Li, Haixiao Xu |
| 2023 | FedGuard: Selective Parameter Aggregation for Poisoning Attack Mitigation in Federated Learning. Melvin Chelli, Cèdric Prigent, René Schubotz, Alexandru Costan, Gabriel Antoniu, Loïc Cudennec, Philipp Slusallek |
| 2023 | FullRepair: Towards Optimal Repair Pipelining in Erasure-Coded Clustered Storage Systems. Yuzuo Zhang, Xinyuan Tu, Lin Wang, Yuchong Hu, Fang Wang, Ye Wang |
| 2023 | GPU Occupancy Prediction of Deep Learning Models Using Graph Neural Network. Hengquan Mei, Huaizhi Qu, Jingwei Sun, Yanjie Gao, Haoxiang Lin, Guangzhong Sun |
| 2023 | Generalized Collective Algorithms for the Exascale Era. Michael Wilkins, Hanming Wang, Peizhi Liu, Bangyen Pham, Yanfei Guo, Rajeev Thakur, Peter A. Dinda, Nikos Hardavellas |
| 2023 | HASpMV: Heterogeneity-Aware Sparse Matrix-Vector Multiplication on Modern Asymmetric Multicore Processors. Wenxuan Li, Helin Cheng, Zhengyang Lu, Yuechen Lu, Weifeng Liu |
| 2023 | HIOS: Hierarchical Inter-Operator Scheduler for Real-Time Inference of DAG-Structured Deep Learning Models on Multiple GPUs. Turja Kundu, Tong Shu |
| 2023 | Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach. Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz |
| 2023 | IEEE International Conference on Cluster Computing, CLUSTER 2023, Santa Fe, NM, USA, October 31 - Nov. 3, 2023 |
| 2023 | JACO: JAva Code Layout Optimizer Enabling Continuous Optimization without Pausing Application Services. Wenhai Lin, Jingchang Qin, Yiquan Chen, Zhen Jin, Jiexiong Xu, Yuzhong Zhang, Shishun Cai, Lirong Fu, Yi Chen, Wenzhi Chen |
| 2023 | KV-CSD: A Hardware-Accelerated Key-Value Store for Data-Intensive Applications. Inhyuk Park, Qing Zheng, Dominic Manno, Soonyeal Yang, Jason Lee, David Bonnie, Bradley W. Settlemyer, Youngjae Kim, Woosuk Chung, Gary Grider |
| 2023 | Optimizing HPC I/O Performance with Regression Analysis and Ensemble Learning. Zhangyu Liu, Cheng Zhang, Huijun Wu, Jianbin Fang, Lin Peng, Guixin Ye, Zhanyong Tang |
| 2023 | Performance Characterization of NVMe Flash Devices with Zoned Namespaces (ZNS). Krijn Doekemeijer, Nick Tehrany, Balakrishnan Chandrasekaran, Matias Bjørling, Animesh Trivedi |
| 2023 | PiP-MColl: Process-in-Process-based Multi-object MPI Collectives. Jiajun Huang, Kaiming Ouyang, Yujia Zhai, Jinyang Liu, Min Si, Ken Raffenetti, Hui Zhou, Atsushi Hori, Zizhong Chen, Yanfei Guo, Rajeev Thakur |
| 2023 | PredictDDL: Reusable Workload Performance Prediction for Distributed Deep Learning. Kevin Assogba, Eduardo Lima, M. Mustafa Rafique, Minseok Kwon |
| 2023 | Prophet: Fine-grained Load Balancing for Parallel Training of Large-scale MoE Models. Wei Wang, Zhiquan Lai, Shengwei Li, Weijie Liu, Keshi Ge, Yujie Liu, Ao Shen, Dongsheng Li |
| 2023 | ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum. Daniel Rosendo, Marta Mattoso, Alexandru Costan, Renan Souza, Débora B. Pina, Patrick Valduriez, Gabriel Antoniu |
| 2023 | Reducing Data Motion and Energy Consumption of Geospatial Modeling Applications Using Automated Precision Conversion. Qinglei Cao, Sameh Abdulah, Hatem Ltaief, Marc G. Genton, David E. Keyes, George Bosilca |
| 2023 | Rethinking Virtual Machines Live Migration for Memory Disaggregation. Xingguo Jia, Xingzi Yu, Yun Wang, Senhao Yu, Zhengwei Qi |
| 2023 | SDT: A Low-cost and Topology-reconfigurable Testbed for Network Research. Zixuan Chen, Zhigao Zhao, Zijian Li, Jiang Shao, Sen Liu, Yang Xu |
| 2023 | SciLance: Mitigate Load Imbalance for Parallel Scientific Applications in Cloud Environments. Xinying Wang, Lipeng Wan, Scott Klasky, Dongfang Zhao, Feng Yan |
| 2023 | TopoCommit: A Topological Commit Protocol for Cross-Ledger Transactions in Scientific Computing. Olamide Timothy Tawose, Lei Yang, Dongfang Zhao |
| 2023 | Uniform Algorithms for Reduce-scatter and (most) other Collectives for MPI. Jesper Larsson Träff, Sascha Hunold, Ioannis Vardas, Nikolaus Manes Funk |