Copertina

Enhancing Lossy Compression Through Cross-Field Information for Scientific Applications

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Youyuan, Jia, Wenqi, Yang, Taolue, Yin, Miao, Jin, Sian
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

KVComp: A High-Performance, LLM-Aware, Lossy Compression Framework for KV Cache
di: Jiang, Bo, et al.
Pubblicazione: (2025)

PackKV: Reducing KV Cache Memory Footprint through LLM-Aware Lossy Compression
di: Jiang, Bo, et al.
Pubblicazione: (2025)

NeurLZ: An Online Neural Learning-Based Method to Enhance Scientific Lossy Compression
di: Jia, Wenqi, et al.
Pubblicazione: (2024)

GWLZ: A Group-wise Learning-based Lossy Compression Framework for Scientific Data
di: Jia, Wenqi, et al.
Pubblicazione: (2024)

FLARE: A Dataflow-Aware and Scalable Hardware Architecture for Neural-Hybrid Scientific Lossy Compression
di: Jia, Wenqi, et al.
Pubblicazione: (2025)

IPComp: Interpolation Based Progressive Lossy Compression for Scientific Applications
di: Yang, Zhuoxun, et al.
Pubblicazione: (2025)

A Survey on Error-Bounded Lossy Compression for Scientific Datasets
di: Di, Sheng, et al.
Pubblicazione: (2024)

DiReDi: Distillation and Reverse Distillation for AIoT Applications
di: Sun, Chen, et al.
Pubblicazione: (2024)

STZ: A High Quality and High Speed Streaming Lossy Compression Framework for Scientific Data
di: Wang, Daoce, et al.
Pubblicazione: (2025)

LCP: Enhancing Scientific Data Management with Lossy Compression for Particles
di: Zhang, Longtao, et al.
Pubblicazione: (2024)

Boosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration
di: Wu, Shixun, et al.
Pubblicazione: (2025)

cuSZ-$i$: High-Ratio Scientific Lossy Compression on GPUs with Optimized Multi-Level Interpolation
di: Liu, Jinyang, et al.
Pubblicazione: (2023)

Preserving Clusters in Error-Bounded Lossy Compression of Particle Data
di: Ren, Congrong, et al.
Pubblicazione: (2026)

ZipMoE: Efficient On-Device MoE Serving via Lossless Compression and Cache-Affinity Scheduling
di: Yang, Yuchen, et al.
Pubblicazione: (2026)

UCCL-Zip: Lossless Compression Supercharged GPU Communication
di: Ma, Shuang, et al.
Pubblicazione: (2026)

FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression
di: Tang, Zhenheng, et al.
Pubblicazione: (2024)

Federated Multi-Objective Learning
di: Yang, Haibo, et al.
Pubblicazione: (2023)

TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training
di: Liu, Man, et al.
Pubblicazione: (2026)

Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
di: Wei, Wenqi, et al.
Pubblicazione: (2024)

CG-FedLLM: How to Compress Gradients in Federated Fune-tuning for Large Language Models
di: Wu, Huiwen, et al.
Pubblicazione: (2024)

Accelerating Communication in Deep Learning Recommendation Model Training with Dual-Level Adaptive Lossy Compression
di: Feng, Hao, et al.
Pubblicazione: (2024)

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
di: Hudson, Nathaniel, et al.
Pubblicazione: (2024)

Bayesian Federated Model Compression for Communication and Computation Efficiency
di: Xia, Chengyu, et al.
Pubblicazione: (2024)

Multimodal Federated Learning with Missing Modality via Prototype Mask and Contrast
di: Bao, Guangyin, et al.
Pubblicazione: (2023)

Adaptive Approach to Enhance Machine Learning Scheduling Algorithms During Runtime Using Reinforcement Learning in Metascheduling Applications
di: Alshaer, Samer, et al.
Pubblicazione: (2025)

Metal-Sci: A Scientific Compute Benchmark for Evolutionary LLM Kernel Search on Apple Silicon
di: Gallego, Víctor
Pubblicazione: (2026)

Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems
di: Miao, Xupeng, et al.
Pubblicazione: (2023)

Communication-Efficient Split Learning via Adaptive Feature-Wise Compression
di: Oh, Yongjeong, et al.
Pubblicazione: (2023)

Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization
di: Li, Yang, et al.
Pubblicazione: (2025)

SplitZip: Ultra Fast Lossless KV Compression for Disaggregated LLM Serving
di: Guo, Yipin, et al.
Pubblicazione: (2026)

RelayGR: Scaling Long-Sequence Generative Recommendation via Cross-Stage Relay-Race Inference
di: Wang, Jiarui, et al.
Pubblicazione: (2026)

To Compress or Not To Compress: Energy Trade-Offs and Benefits of Lossy Compressed I/O
di: Wilkins, Grant, et al.
Pubblicazione: (2024)

SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile
di: Niu, Wei, et al.
Pubblicazione: (2024)

Role-Based Fault Tolerance System for LLM RL Post-Training
di: Chen, Zhenqian, et al.
Pubblicazione: (2025)

GraphGen+: Advancing Distributed Subgraph Generation and Graph Learning On Industrial Graphs
di: Jin, Yue, et al.
Pubblicazione: (2025)

Efficient Federated Learning with Timely Update Dissemination
di: Jia, Juncheng, et al.
Pubblicazione: (2025)

Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management
di: Zhang, Yifan, et al.
Pubblicazione: (2024)

TrainVerify: Equivalence-Based Verification for Distributed LLM Training
di: Lu, Yunchi, et al.
Pubblicazione: (2025)

Efficient Serving of LLM Applications with Probabilistic Demand Modeling
di: Liu, Yifei, et al.
Pubblicazione: (2025)

HybridEP: Scaling Expert Parallelism to Cross-Datacenter Scenario via Hybrid Expert/Data Transmission
di: Yang, Weihao, et al.
Pubblicazione: (2025)