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ORCID31st HiPC 2024: Bangalore, India
- 31st IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2024, Bangalore, India, December 18-21, 2024. IEEE 2024, ISBN 979-8-3315-0909-5
- Robin Boëzennec, Danilo Carastan-Santos, Fanny Dufossé, Guillaume Pallez:
Allocation Strategies for Disaggregated Memory in HPC Systems. 1-11 - Abrar Hossain, Abdel-Hameed A. Badawy, Mohammad A. Islam
, Tapasya Patki, Kishwar Ahmed:
HPC Application Parameter Autotuning on Edge Devices: A Bandit Learning Approach. 12-22 - Benjamin Michalowicz, Kaushik Kandadi Suresh, Hari Subramoni, Mustafa Abduljabbar, Dhabaleswar K. Panda, Steve Poole:
Effective and Efficient Offloading Designs for One-Sided Communication to SmartNICs. 23-33 - Zhibo Xuan, Xin You, Hailong Yang, Mingzhen Li, Zhongzhi Luan, Yi Liu, Depei Qian:
Retrospection on the Performance Analysis Tools for Large-Scale HPC Programs. 34-44 - Anastasia Khartikova, Denis Shaikhislamov, Ilya Timokhin, Roman Kostromin, Vladislav Muratov, Aleksey Demakov, Maxim Belov, Aleksey Teplov:
BigThrill: MPI-based Data Processing Engine. 45-56 - Lang Xu, Quentin Anthony, Jacob Hatef, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning. 57-67 - Aryan Kumar Singh, Arpit Saikia, Pranita Baro, Malaya Dutta Borah:
Transformer-based Self-Supervised Imputation and Attention GANs Oversampling for Medical Data Processing. 68-77 - Changxin Li, Sanmukh Kuppannagari:
Exploring Algorithmic Design Choices for Low Latency CNN Deployment. 78-88 - Ashwin Krishnan, Venkatesh Pasumarti, Samarth Inamdar, Arghyajoy Mondal, Manoj Nambiar, Rekha Singhal:
CAR-LLM: Cloud Accelerator Recommender for Large Language Models. 89-99 - Nawras Alnaasan, Bharath Ramesh, Jinghan Yao, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
HyperSack: Distributed Hyperparameter Optimization for Deep Learning using Resource-Aware Scheduling on Heterogeneous GPU Systems. 100-110 - Revanth Reddy Munugala, Michael Gowanlock:
GDBOD: Density-Based Outlier Detection Exploiting Efficient Tree Traversals on the GPU. 111-121 - Chen-Chun Chen, Goutham Kalikrishna Reddy Kuncham, Hari Subramoni, Dhabaleswar K. Panda:
Design and Implementation of Kernel-based MPI Reduction Operations for Intel GPU s. 122-131 - Brian Donnelly, Michael Gowanlock:
Multi-Space Tree with Incremental Construction for GPU-Accelerated Range Queries. 132-142 - Andrew Geyko, Gerald Collom, Derek Schafer, Patrick G. Bridges, Amanda Bienz:
A More Scalable Sparse Dynamic Data Exchange. 143-154 - Kaushik Kandadi Suresh, Benjamin Michalowicz, Nick Contini, Bharath Ramesh, Mustafa Abduljabbar, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Using BlueField-3 SmartNICs to Offload Vector Operations in Krylov Subspace Methods. 155-165 - Sudhanshu Pravin Kulkarni, E. Wes Bethel:
From Bits to Qubits: Challenges in Classical-Quantum Integration. 166-176 - Kartikey Sarode:
Circuit Partitioning and Full Circuit Execution: A Comparative Study of GPU - Based Quantum Circuit Simulation. 177-187 - Bo Zhang, Philip E. Davis, Zhao Zhang, Keita Teranishi, Manish Parashar:
Dual Channel Dual Staging: Hierarchical and Portable Staging for GPU-Based In-Situ Workflow. 188-198 - Samuel Curtis, Harry Waugh, Tom Deakin, Gihan R. Mudalige:
Mini-Combust - An Open-Source Unstructured FGM Combustion Mini-App for Co-Designing Aero-Engines at Extreme Scale. 199-209 - Andy Wolff, Avinash Karanth:
Training Photonic Mach Zehnder Meshes for Neural Network Acceleration. 210-220 - Yiheng Xu, Pranav Sivaraman, Hariharan Devarajan, Kathryn M. Mohror, Abhinav Bhatele:
ML-based Modeling to Predict I/O Performance on Different Storage Sub-systems. 221-231 - Julien Monniot, François Tessier, Henri Casanova, Gabriel Antoniu:
Simulation of Large-Scale HPC Storage Systems: Challenges and Methodologies. 232-242 - S. Haleh S. Dizaji, Reza Farahani, Joze M. Rozanec, Dragi Kimovski, Ahmet Soylu, Radu Prodan:
Graph Sampling Quality Prediction for Algorithm Recommendation. 243-254 - Cèdric Prigent, Melvin Chelli, Alexandru Costan, Loïc Cudennec, René Schubotz, Gabriel Antoniu:
Efficient Resource-Constrained Federated Learning Clustering with Local Data Compression on the Edge-to-Cloud Continuum. 255-265 - Advik Raj Basani, Siddharth Chaitra Vivek, Advaith Krishna, Arnab K. Paul:
When Less is More: Achieving Faster Convergence in Distributed Edge Machine Learning. 266-276 - Rahulkumar Gayatri, Shilei Tian, Stephen L. Olivier, Eric Wright, Johannes Doerfert:
Leveraging LLVM OpenMP GPU Offload Optimizations for Kokkos Applications. 277-287
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