FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications
Fuente:
arXiv
Saved in:
| Main Authors: | Wilkins, Grant, Di, Sheng, Calhoun, Jon C., Li, Zilinghan, Kim, Kibaek, Underwood, Robert, Mortier, Richard, Cappello, Franck |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
To Compress or Not To Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O
by: Wilkins, Grant, et al.
Published: (2024)
by: Wilkins, Grant, et al.
Published: (2024)
A Survey on Error-Bounded Lossy Compression for Scientific Datasets
by: Di, Sheng, et al.
Published: (2024)
by: Di, Sheng, et al.
Published: (2024)
Preserving Clusters in Error-Bounded Lossy Compression of Particle Data
by: Ren, Congrong, et al.
Published: (2026)
by: Ren, Congrong, et al.
Published: (2026)
cuSZ-$i$: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation
by: Liu, Jinyang, et al.
Published: (2023)
by: Liu, Jinyang, et al.
Published: (2023)
ZCCL: Significantly Improving Collective Communication With Error-Bounded Lossy Compression
by: Huang, Jiajun, et al.
Published: (2025)
by: Huang, Jiajun, et al.
Published: (2025)
Boosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration
by: Wu, Shixun, et al.
Published: (2025)
by: Wu, Shixun, et al.
Published: (2025)
HoSZp: An Efficient Homomorphic Error-bounded Lossy Compressor for Scientific Data
by: Agarwal, Tripti, et al.
Published: (2024)
by: Agarwal, Tripti, et al.
Published: (2024)
FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud
by: Sinha, Aditya, et al.
Published: (2025)
by: Sinha, Aditya, et al.
Published: (2025)
pMSz: A Distributed Parallel Algorithm for Correcting Extrema and Morse Smale Segmentations in Lossy Compression
by: Li, Yuxiao, et al.
Published: (2026)
by: Li, Yuxiao, et al.
Published: (2026)
QPET: A Versatile and Portable Quantity-of-Interest-Preservation Framework for Error-Bounded Lossy Compression
by: Liu, Jinyang, et al.
Published: (2024)
by: Liu, Jinyang, et al.
Published: (2024)
An Optimized Error-controlled MPI Collective Framework Integrated with Lossy Compression
by: Huang, Jiajun, et al.
Published: (2023)
by: Huang, Jiajun, et al.
Published: (2023)
IPComp: Interpolation Based Progressive Lossy Compression for Scientific Applications
by: Yang, Zhuoxun, et al.
Published: (2025)
by: Yang, Zhuoxun, et al.
Published: (2025)
DeepCQ: General-Purpose Deep-Surrogate Framework for Lossy Compression Quality Prediction
by: Mumenin, Khondoker Mirazul, et al.
Published: (2025)
by: Mumenin, Khondoker Mirazul, et al.
Published: (2025)
FFCz: Fast Fourier Correction for Spectrum-Preserving Lossy Compression of Scientific Data
by: Ren, Congrong, et al.
Published: (2026)
by: Ren, Congrong, et al.
Published: (2026)
FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training
by: Li, Yijiang, et al.
Published: (2026)
by: Li, Yijiang, et al.
Published: (2026)
Offline Energy-Optimal LLM Serving: Workload-Based Energy Models for LLM Inference on Heterogeneous Systems
by: Wilkins, Grant, et al.
Published: (2024)
by: Wilkins, Grant, et al.
Published: (2024)
An Efficient Gradient-Aware Error-Bounded Lossy Compressor for Federated Learning
by: Ye, Zhijing, et al.
Published: (2025)
by: Ye, Zhijing, et al.
Published: (2025)
TopoSZp: Lightweight Topology-Aware Error-controlled Compression for Scientific Data
by: Agarwal, Tripti, et al.
Published: (2026)
by: Agarwal, Tripti, et al.
Published: (2026)
Experiences Building Enterprise-Level Privacy-Preserving Federated Learning to Power AI for Science
by: Li, Zilinghan, et al.
Published: (2025)
by: Li, Zilinghan, et al.
Published: (2025)
LCP: Enhancing Scientific Data Management with Lossy Compression for Particles
by: Zhang, Longtao, et al.
Published: (2024)
by: Zhang, Longtao, et al.
Published: (2024)
Rate-Distortion Bounds for Heterogeneous Random Fields on Finite Lattices
by: Sinha, Sujata, et al.
Published: (2026)
by: Sinha, Sujata, et al.
Published: (2026)
GPZ: GPU-Accelerated Lossy Compressor for Particle Data
by: Li, Ruoyu, et al.
Published: (2025)
by: Li, Ruoyu, et al.
Published: (2025)
Hybrid Heterogeneous Clusters Can Lower the Energy Consumption of LLM Inference Workloads
by: Wilkins, Grant, et al.
Published: (2024)
by: Wilkins, Grant, et al.
Published: (2024)
High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation
by: Liu, Jinyang, et al.
Published: (2023)
by: Liu, Jinyang, et al.
Published: (2023)
Lessons Learned on the Path to Guaranteeing the Error Bound in Lossy Quantizers
by: Fallin, Alex, et al.
Published: (2024)
by: Fallin, Alex, et al.
Published: (2024)
Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System
by: Madduri, Ravi, et al.
Published: (2024)
by: Madduri, Ravi, et al.
Published: (2024)
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler
by: Li, Zilinghan, et al.
Published: (2023)
by: Li, Zilinghan, et al.
Published: (2023)
DGRO: Diameter-Guided Ring Optimization for Integrated Research Infrastructure Membership
by: Wu, Shixun, et al.
Published: (2024)
by: Wu, Shixun, et al.
Published: (2024)
gZCCL: Compression-Accelerated Collective Communication Framework for GPU Clusters
by: Huang, Jiajun, et al.
Published: (2023)
by: Huang, Jiajun, et al.
Published: (2023)
Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources -- A Case Study on Federated Fine-tuning of LLaMA 2
by: Li, Zilinghan, et al.
Published: (2024)
by: Li, Zilinghan, et al.
Published: (2024)
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
by: Li, Zilinghan, et al.
Published: (2024)
by: Li, Zilinghan, et al.
Published: (2024)
EcoFed: Efficient Communication for DNN Partitioning-based Federated Learning
by: Wu, Di, et al.
Published: (2023)
by: Wu, Di, et al.
Published: (2023)
A Data-Informed Local Subspaces Method for Error-Bounded Lossy Compression of Large-Scale Scientific Datasets
by: Khan, Arshan, et al.
Published: (2026)
by: Khan, Arshan, et al.
Published: (2026)
DataStates-LLM: Lazy Asynchronous Checkpointing for Large Language Models
by: Maurya, Avinash, et al.
Published: (2024)
by: Maurya, Avinash, et al.
Published: (2024)
MSz: An Efficient Parallel Algorithm for Correcting Morse-Smale Segmentations in Error-Bounded Lossy Compressors
by: Li, Yuxiao, et al.
Published: (2024)
by: Li, Yuxiao, et al.
Published: (2024)
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays
by: Iakovidou, Charikleia, et al.
Published: (2024)
by: Iakovidou, Charikleia, et al.
Published: (2024)
SPARe: Stacked Parallelism with Adaptive Reordering for Fault-Tolerant LLM Pretraining Systems with 100k+ GPUs
by: Lee, Jin, et al.
Published: (2026)
by: Lee, Jin, et al.
Published: (2026)
Mitigating Artifacts in Pre-quantization Based Scientific Data Compressors with Quantization-aware Interpolation
by: Jiao, Pu, et al.
Published: (2026)
by: Jiao, Pu, et al.
Published: (2026)
PackKV: Reducing KV Cache Memory Footprint through LLM-Aware Lossy Compression
by: Jiang, Bo, et al.
Published: (2025)
by: Jiang, Bo, et al.
Published: (2025)
TurboFFT: A High-Performance Fast Fourier Transform with Fault Tolerance on GPU
by: Wu, Shixun, et al.
Published: (2024)
by: Wu, Shixun, et al.
Published: (2024)
Similar Items
-
To Compress or Not To Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O
by: Wilkins, Grant, et al.
Published: (2024) -
A Survey on Error-Bounded Lossy Compression for Scientific Datasets
by: Di, Sheng, et al.
Published: (2024) -
Preserving Clusters in Error-Bounded Lossy Compression of Particle Data
by: Ren, Congrong, et al.
Published: (2026) -
cuSZ-$i$: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation
by: Liu, Jinyang, et al.
Published: (2023) -
ZCCL: Significantly Improving Collective Communication With Error-Bounded Lossy Compression
by: Huang, Jiajun, et al.
Published: (2025)