Imagen de Portada

Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Banerjee, Roopkatha, Chandrashekar, Tejus, Eswar, Ananth, Simmhan, Yogesh
Formato:	Preprint
Publicado:	2025
Materias:	Distributed, Parallel, and Cluster Computing
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources
por: Banerjee, Roopkatha, et al.
Publicado: (2025)

Understanding the Performance and Power of LLM Inferencing on Edge Accelerators
por: Arya, Mayank, et al.
Publicado: (2025)

Evaluating Multi-Instance DNN Inferencing on Multiple Accelerators of an Edge Device
por: Tayal, Mumuksh, et al.
Publicado: (2025)

Optimizing Federated Learning for Scalable Power-demand Forecasting in Microgrids
por: Banerjee, Roopkatha, et al.
Publicado: (2025)

Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models
por: K., Prashanthi S., et al.
Publicado: (2025)

OptimES: Optimizing Federated Learning Using Remote Embeddings for Graph Neural Networks
por: Naman, Pranjal, et al.
Publicado: (2025)

Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators
por: K., Prashanthi S., et al.
Publicado: (2023)

Pagoda: An Energy and Time Roofline Study for DNN Workloads on Edge Accelerators
por: K., Prashanthi S., et al.
Publicado: (2025)

Optimizing Federated Learning using Remote Embeddings for Graph Neural Networks
por: Naman, Pranjal, et al.
Publicado: (2025)

AerialDB: A Federated Peer-to-Peer Spatio-temporal Edge Datastore for Drone Fleets
por: Jaiswal, Shashwat, et al.
Publicado: (2025)

Ripple: Scalable Incremental GNN Inferencing on Large Streaming Graphs
por: Naman, Pranjal, et al.
Publicado: (2025)

ATLAS: Efficient Out-of-Core Inference for Billion-Scale Graph Neural Networks
por: Naman, Pranjal, et al.
Publicado: (2026)

Adaptive Heuristics for Scheduling DNN Inferencing on Edge and Cloud for Personalized UAV Fleets
por: Raj, Suman, et al.
Publicado: (2024)

Scaling Real-Time Traffic Analytics on Edge-Cloud Fabrics for City-Scale Camera Networks
por: Sharma, Akash, et al.
Publicado: (2026)

AeroGen: Agentic Drone Autonomy through Single-Shot Structured Prompting & Drone SDK
por: Astu, Kautuk, et al.
Publicado: (2026)

Fulcrum: Optimizing Concurrent DNN Training and Inferencing on Edge Accelerators
por: K., Prashanthi S., et al.
Publicado: (2025)

D3FL: Data Distribution and Detrending for Robust Federated Learning in Non-linear Time-series Data
por: Marisetty, Harsha Varun, et al.
Publicado: (2025)

AeroDaaS: Towards an Application Programming Framework for Drones-as-a-Service
por: Raj, Suman, et al.
Publicado: (2025)

RIPPLE++: An Incremental Framework for Efficient GNN Inference on Evolving Graphs
por: Naman, Pranjal, et al.
Publicado: (2026)

AeroDaaS: A Programmable Drones-as-a-Service Platform for Intelligent Aerial Systems
por: Astu, Kautuk, et al.
Publicado: (2026)

AeroResQ: Edge-Accelerated UAV Framework for Scalable, Resilient and Collaborative Escape Route Planning in Wildfire Scenarios
por: Raj, Suman, et al.
Publicado: (2025)

A Blockchain-Enabled Framework for Storage and Retrieval of Social Data
por: Parab, Aishwarya, et al.
Publicado: (2025)

PowerTrain: Fast, Generalizable Time and Power Prediction Models to Optimize DNN Training on Accelerated Edges
por: K., Prashanthi S., et al.
Publicado: (2024)

Federated Learning as a Service for Hierarchical Edge Networks with Heterogeneous Models
por: Gao, Wentao, et al.
Publicado: (2024)

Characterizing FaaS Workflows on Public Clouds: The Good, the Bad and the Ugly
por: Kulkarni, Varad, et al.
Publicado: (2025)

Optimizing FaaS Platforms for MCP-enabled Agentic Workflows
por: Kulkarni, Varad, et al.
Publicado: (2026)

Collaborative Processing for Multi-Tenant Inference on Memory-Constrained Edge TPUs
por: Ng, Nathan, et al.
Publicado: (2026)

AgentX: Towards Orchestrating Robust Agentic Workflow Patterns with FaaS-hosted MCP Services
por: Tokal, Shiva Sai Krishna Anand, et al.
Publicado: (2025)

Ocularone-Bench: Benchmarking DNN Models on GPUs to Assist the Visually Impaired
por: Raj, Suman, et al.
Publicado: (2025)

CroSatFL: Energy-Efficient Federated Learning with Cross-Aggregation for Satellite Edge Computing
por: Yang, Nan, et al.
Publicado: (2026)

Energy Efficient Federated Learning with Hyperdimensional Computing over Wireless Communication Networks
por: Ding, Yahao, et al.
Publicado: (2026)

Decentralized LLM Inference over Edge Networks with Energy Harvesting
por: Khoshsirat, Aria, et al.
Publicado: (2024)

Resource-efficient Parallel Split Learning in Heterogeneous Edge Computing
por: Zhang, Mingjin, et al.
Publicado: (2024)

End-to-End and Phase-Level Performance Optimization for Hyperledger Fabric
por: Sollu, Pavan, et al.
Publicado: (2026)

A Joint Time and Energy-Efficient Federated Learning-based Computation Offloading Method for Mobile Edge Computing
por: Mukherjee, Anwesha, et al.
Publicado: (2024)

Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System
por: Ching, Cheng-Wei, et al.
Publicado: (2026)

Lightweight Federated Learning over Wireless Edge Networks
por: Hou, Xiangwang, et al.
Publicado: (2025)

Analysis and Optimization of Wireless Multimodal Federated Learning on Modal Heterogeneity
por: Han, Xuefeng, et al.
Publicado: (2025)

Exploring System-Heterogeneous Federated Learning with Dynamic Model Selection
por: Yao, Dixi
Publicado: (2024)

Bridging Memory Gaps: Scaling Federated Learning for Heterogeneous Clients
por: Wu, Yebo, et al.
Publicado: (2024)