:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Haghshenas, Kawsar, Hashemi, Mona
Format:	Preprint
Published:	2024
Subjects:	Distributed, Parallel, and Cluster Computing
Online Access:	https://arxiv.org/abs/2412.08294
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Salted Inference: Enhancing Privacy while Maintaining Efficiency of Split Inference in Mobile Computing
by: Malekzadeh, Mohammad, et al.
Published: (2023)

A Dynamic Approach to Load Balancing in Cloud Infrastructure: Enhancing Energy Efficiency and Resource Utilization
by: Sakib, Shadman, et al.
Published: (2025)

Training DNN Models over Heterogeneous Clusters with Optimal Performance
by: Nie, Chengyi, et al.
Published: (2024)

Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances
by: Duan, Jiangfei, et al.
Published: (2024)

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

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

SWIFT: Expedited Failure Recovery for Large-scale DNN Training
by: Zhong, Yuchen, et al.
Published: (2023)

ParvaGPU: Efficient Spatial GPU Sharing for Large-Scale DNN Inference in Cloud Environments
by: Lee, Munkyu, et al.
Published: (2024)

Nezha: Breaking Multi-Rail Network Barriers for Distributed DNN Training
by: Yu, Enda, et al.
Published: (2024)

Poplar: Efficient Scaling of Distributed DNN Training on Heterogeneous GPU Clusters
by: Zhang, WenZheng, et al.
Published: (2024)

A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training
by: Jiang, Lijuan, et al.
Published: (2025)

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

Optimizing Resource Allocation and Energy Efficiency in Federated Fog Computing for IoT
by: Shah, Syed Sarmad, et al.
Published: (2025)

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis
by: Zhang, Shiwei, et al.
Published: (2024)

AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices
by: Lin, Zheng, et al.
Published: (2024)

A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO
by: Svedas, Jonas, et al.
Published: (2025)

Collaborative Inference in DNN-based Satellite Systems with Dynamic Task Streams
by: Guan, Jinglong, et al.
Published: (2023)

The Case for Time-Shared Computing Resources
by: Jacquet, Pierre, et al.
Published: (2025)

Memory Efficient and Staleness Free Pipeline Parallel DNN Training Framework with Improved Convergence Speed
by: Dutta, Ankita, et al.
Published: (2025)

GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory Stitching
by: Guo, Cong, et al.
Published: (2024)

TiMePReSt: Time and Memory Efficient Pipeline Parallel DNN Training with Removed Staleness
by: Dutta, Ankita, et al.
Published: (2024)

Infer-EDGE: Dynamic DNN Inference Optimization in 'Just-in-time' Edge-AI Implementations
by: Mounesan, Motahare, et al.
Published: (2025)

Shared Virtual Memory: Its Design and Performance Implications for Diverse Applications
by: Cooper, Bennett, et al.
Published: (2024)

Modality Inflation: Energy Characterization and Optimization Opportunities for MLLM Inference
by: Moghadampanah, Mona, et al.
Published: (2025)

PaSE: Parallelization Strategies for Efficient DNN Training
by: Elango, Venmugil
Published: (2024)

AdaBridge: Dynamic Data and Computation Reuse for Efficient Multi-task DNN Co-evolution in Edge Systems
by: Wang, Lehao, et al.
Published: (2024)

Optimal Resource Efficiency with Fairness in Heterogeneous GPU Clusters
by: Mo, Zizhao, et al.
Published: (2024)

Dynamic Service Scheduling and Resource Management in Energy-Harvesting Multi-access Edge Computing
by: Chen, Shuyi, et al.
Published: (2025)

Boosting LLM Serving through Spatial-Temporal GPU Resource Sharing
by: Lin, Zejia, et al.
Published: (2025)

Workload Buoyancy: Keeping Apps Afloat by Identifying Shared Resource Bottlenecks
by: Larsson, Oliver, et al.
Published: (2026)

Schedule-Level Shared-Prefix Reuse for LLM RL Training
by: Li, Pengbo, et al.
Published: (2026)

EdgeServing: Deadline-Aware Multi-DNN Serving at the Edge
by: Cao, Jiahe, et al.
Published: (2026)

Blockchain-enabled Energy Trading and Battery-based Sharing in Microgrids
by: Zekiye, Abdulrezzak, et al.
Published: (2024)

DRust: Language-Guided Distributed Shared Memory with Fine Granularity, Full Transparency, and Ultra Efficiency
by: Ma, Haoran, et al.
Published: (2024)

Collaborative Satellite Computing through Adaptive DNN Task Splitting and Offloading
by: Peng, Shifeng, et al.
Published: (2024)

Online Optimization of DNN Inference Network Utility in Collaborative Edge Computing
by: Li, Rui, et al.
Published: (2024)

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

EcoFed: Efficient Communication for DNN Partitioning-based Federated Learning
by: Wu, Di, et al.
Published: (2023)

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

A Scalable State Sharing Protocol for Low-Resource Validator Nodes in Blockchain Networks
by: Hias, Ruben, et al.
Published: (2024)