Copertina

EarthSight: A Distributed Framework for Low-Latency Satellite Intelligence

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Erol, Ansel Kaplan, Lee, Seungjun, Mahajan, Divya
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Equinox: Decentralized Scheduling for Hardware-Aware Orbital Intelligence
di: Erol, Ansel Kaplan, et al.
Pubblicazione: (2026)

MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing
di: Go, Seokjin, et al.
Pubblicazione: (2025)

NEST: Network- and Memory-Aware Device Placement For Distributed Deep Learning
di: Wang, Irene, et al.
Pubblicazione: (2026)

Characterizing the Efficiency of Distributed Training: A Power, Performance, and Thermal Perspective
di: Go, Seokjin, et al.
Pubblicazione: (2025)

Intelligent Task Offloading in VANETs: A Hybrid AI-Driven Approach for Low-Latency and Energy Efficiency
di: Qayyum, Tariq, et al.
Pubblicazione: (2025)

ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving
di: Go, Seokjin, et al.
Pubblicazione: (2026)

OMEGA: A Low-Latency GNN Serving System for Large Graphs
di: Kim, Geon-Woo, et al.
Pubblicazione: (2025)

ServerlessLLM: Low-Latency Serverless Inference for Large Language Models
di: Fu, Yao, et al.
Pubblicazione: (2024)

Large-Scale Graph Building in Dynamic Environments: Low Latency and High Quality
di: de Almeida, Filipe Miguel Gonçalves, et al.
Pubblicazione: (2025)

SwiftSpec: Ultra-Low Latency LLM Decoding by Scaling Asynchronous Speculative Decoding
di: Zhang, Ziyi, et al.
Pubblicazione: (2025)

Integrated Hardware Architecture and Device Placement Search
di: Wang, Irene, et al.
Pubblicazione: (2024)

OpenDiLoCo: An Open-Source Framework for Globally Distributed Low-Communication Training
di: Jaghouar, Sami, et al.
Pubblicazione: (2024)

A Semi-Supervised Federated Learning Framework with Hierarchical Clustering Aggregation for Heterogeneous Satellite Networks
di: Liu, Zhuocheng, et al.
Pubblicazione: (2025)

GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters
di: Song, Jaeyong, et al.
Pubblicazione: (2023)

Intelligent Orchestration of Distributed Large Foundation Model Inference at the Edge
di: Koch, Fernando, et al.
Pubblicazione: (2025)

Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning
di: Elmahallawy, Mohamed, et al.
Pubblicazione: (2024)

Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve
di: Agrawal, Amey, et al.
Pubblicazione: (2024)

SDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks
di: Huang, Xin, et al.
Pubblicazione: (2024)

Characterizing Compute-Communication Overlap in GPU-Accelerated Distributed Deep Learning: Performance and Power Implications
di: Lee, Seonho, et al.
Pubblicazione: (2025)

Traversal Learning: A Lossless And Efficient Distributed Learning Framework
di: Batbaatar, Erdenebileg, et al.
Pubblicazione: (2025)

Apparate: Rethinking Early Exits to Tame Latency-Throughput Tensions in ML Serving
di: Dai, Yinwei, et al.
Pubblicazione: (2023)

A Distributed Framework for Causal Modeling of Performance Variability in GPU Traces
di: Lahiry, Ankur, et al.
Pubblicazione: (2025)

Low-Communication Resilient Distributed Estimation Algorithm Based on Memory Mechanism
di: Li, Wei, et al.
Pubblicazione: (2025)

Fair Distributed Cooperative Bandit Learning on Networks for Intelligent Internet of Things Systems (Technical Report)
di: Chen, Ziqun, et al.
Pubblicazione: (2024)

ServerlessLoRA: Minimizing Latency and Cost in Serverless Inference for LoRA-Based LLMs
di: Sui, Yifan, et al.
Pubblicazione: (2025)

Scheduling for On-Board Federated Learning with Satellite Clusters
di: Razmi, Nasrin, et al.
Pubblicazione: (2024)

AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes
di: Xiao, Youshao, et al.
Pubblicazione: (2024)

Canzona: A Unified, Asynchronous, and Load-Balanced Framework for Distributed Matrix-based Optimizers
di: Wang, Liangyu, et al.
Pubblicazione: (2026)

Towards Federated Low-Rank Adaptation of Language Models with Rank Heterogeneity
di: Byun, Yuji, et al.
Pubblicazione: (2024)

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning
di: Song, Jingwei, et al.
Pubblicazione: (2026)

Distributed Stochastic Gradient Descent with Staleness: A Stochastic Delay Differential Equation Based Framework
di: Yu, Siyuan, et al.
Pubblicazione: (2024)

BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences
di: Sun, Ao, et al.
Pubblicazione: (2024)

AERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions
di: Hatanpää, Väinö, et al.
Pubblicazione: (2025)

Distributed Inference on Mobile Edge and Cloud: An Early Exit based Clustering Approach
di: Bajpai, Divya Jyoti, et al.
Pubblicazione: (2024)

BOOST: BOttleneck-Optimized Scalable Training Framework for Low-Rank Large Language Models
di: Wang, Zhengyang, et al.
Pubblicazione: (2025)

Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not?
di: Zhao, Yi, et al.
Pubblicazione: (2026)

Cornserve: A Distributed Serving System for Any-to-Any Multimodal Models
di: Chung, Jae-Won, et al.
Pubblicazione: (2026)

Prediction-Assisted Online Distributed Deep Learning Workload Scheduling in GPU Clusters
di: Luo, Ziyue, et al.
Pubblicazione: (2025)

Efficient Parallel Reinforcement Learning Framework using the Reactor Model
di: Kwok, Jacky, et al.
Pubblicazione: (2023)

A Survey on Collaborative DNN Inference for Edge Intelligence
di: Ren, Weiqing, et al.
Pubblicazione: (2022)