Training DNN Models over Heterogeneous Clusters with Optimal Performance
Fuente:
arXiv
Saved in:
| Main Authors: | Nie, Chengyi, Maghakian, Jessica, Liu, Zhenhua |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Aladdin: Joint Placement and Scaling for SLO-Aware LLM Serving
by: Nie, Chengyi, et al.
Published: (2024)
by: Nie, Chengyi, et al.
Published: (2024)
Poplar: Efficient Scaling of Distributed DNN Training on Heterogeneous GPU Clusters
by: Zhang, WenZheng, et al.
Published: (2024)
by: Zhang, WenZheng, et al.
Published: (2024)
HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis
by: Zhang, Shiwei, et al.
Published: (2024)
by: Zhang, Shiwei, et al.
Published: (2024)
HexiScale: Facilitating Large Language Model Training over Heterogeneous Hardware
by: Yan, Ran, et al.
Published: (2024)
by: Yan, Ran, et al.
Published: (2024)
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators
by: K., Prashanthi S., et al.
Published: (2023)
by: K., Prashanthi S., et al.
Published: (2023)
Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters
by: Strati, Foteini, et al.
Published: (2025)
by: Strati, Foteini, et al.
Published: (2025)
Cephalo: Harnessing Heterogeneous GPU Clusters for Training Transformer Models
by: Guo, Runsheng Benson, et al.
Published: (2024)
by: Guo, Runsheng Benson, et al.
Published: (2024)
Optimal Resource Efficiency with Fairness in Heterogeneous GPU Clusters
by: Mo, Zizhao, et al.
Published: (2024)
by: Mo, Zizhao, et al.
Published: (2024)
SWIFT: Expedited Failure Recovery for Large-scale DNN Training
by: Zhong, Yuchen, et al.
Published: (2023)
by: Zhong, Yuchen, et al.
Published: (2023)
HarmonyBatch: Batching multi-SLO DNN Inference with Heterogeneous Serverless Functions
by: Chen, Jiabin, et al.
Published: (2024)
by: Chen, Jiabin, et al.
Published: (2024)
H2:Towards Efficient Large-Scale LLM Training on Hyper-Heterogeneous Cluster over 1,000 Chips
by: Tang, Ding, et al.
Published: (2025)
by: Tang, Ding, et al.
Published: (2025)
HARP: Orchestrating Automated Parallel Training on Heterogeneous GPU Clusters
by: Liang, Antian, et al.
Published: (2025)
by: Liang, Antian, et al.
Published: (2025)
Zorse: Optimizing LLM Training Efficiency on Heterogeneous GPU Clusters
by: Guo, Runsheng Benson, et al.
Published: (2025)
by: Guo, Runsheng Benson, et al.
Published: (2025)
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO
by: Svedas, Jonas, et al.
Published: (2025)
by: Svedas, Jonas, et al.
Published: (2025)
Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances
by: Duan, Jiangfei, et al.
Published: (2024)
by: Duan, Jiangfei, et al.
Published: (2024)
Fulcrum: Optimizing Concurrent DNN Training and Inferencing on Edge Accelerators
by: K., Prashanthi S., et al.
Published: (2025)
by: K., Prashanthi S., et al.
Published: (2025)
Nezha: Breaking Multi-Rail Network Barriers for Distributed DNN Training
by: Yu, Enda, et al.
Published: (2024)
by: Yu, Enda, et al.
Published: (2024)
A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training
by: Jiang, Lijuan, et al.
Published: (2025)
by: Jiang, Lijuan, et al.
Published: (2025)
Frenzy: A Memory-Aware Serverless LLM Training System for Heterogeneous GPU Clusters
by: Chang, Zihan, et al.
Published: (2024)
by: Chang, Zihan, et al.
Published: (2024)
HexiSeq: Accommodating Long Context Training of LLMs over Heterogeneous Hardware
by: Liang, Yan, et al.
Published: (2026)
by: Liang, Yan, et al.
Published: (2026)
EaCO: Resource Sharing Dynamics and Its Impact on Energy Efficiency for DNN Training
by: Haghshenas, Kawsar, et al.
Published: (2024)
by: Haghshenas, Kawsar, et al.
Published: (2024)
GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory Stitching
by: Guo, Cong, et al.
Published: (2024)
by: Guo, Cong, et al.
Published: (2024)
Memory Efficient and Staleness Free Pipeline Parallel DNN Training Framework with Improved Convergence Speed
by: Dutta, Ankita, et al.
Published: (2025)
by: Dutta, Ankita, et al.
Published: (2025)
DistTrain: Addressing Model and Data Heterogeneity with Disaggregated Training for Multimodal Large Language Models
by: Zhang, Zili, et al.
Published: (2024)
by: Zhang, Zili, et al.
Published: (2024)
TiMePReSt: Time and Memory Efficient Pipeline Parallel DNN Training with Removed Staleness
by: Dutta, Ankita, et al.
Published: (2024)
by: Dutta, Ankita, et al.
Published: (2024)
Enabling Large Batch Size Training for DNN Models Beyond the Memory Limit While Maintaining Performance
by: Piao, XinYu, et al.
Published: (2021)
by: Piao, XinYu, et al.
Published: (2021)
Practical Performance Guarantees for Pipelined DNN Inference
by: Archer, Aaron, et al.
Published: (2023)
by: Archer, Aaron, et al.
Published: (2023)
Ocularone-Bench: Benchmarking DNN Models on GPUs to Assist the Visually Impaired
by: Raj, Suman, et al.
Published: (2025)
by: Raj, Suman, et al.
Published: (2025)
Dalek: An Unconventional and Energy-Aware Heterogeneous Cluster
by: Cassagne, Adrien, et al.
Published: (2025)
by: Cassagne, Adrien, et al.
Published: (2025)
EdgeServing: Deadline-Aware Multi-DNN Serving at the Edge
by: Cao, Jiahe, et al.
Published: (2026)
by: Cao, Jiahe, et al.
Published: (2026)
Cronus: Efficient LLM inference on Heterogeneous GPU Clusters via Partially Disaggregated Prefill
by: Liu, Yunzhao, et al.
Published: (2025)
by: Liu, Yunzhao, et al.
Published: (2025)
HexGen: Generative Inference of Large Language Model over Heterogeneous Environment
by: Jiang, Youhe, et al.
Published: (2023)
by: Jiang, Youhe, et al.
Published: (2023)
Holmes: Towards Distributed Training Across Clusters with Heterogeneous NIC Environment
by: Yang, Fei, et al.
Published: (2023)
by: Yang, Fei, et al.
Published: (2023)
Hamava: Fault-tolerant Reconfigurable Geo-Replication on Heterogeneous Clusters
by: Mane, Tejas, et al.
Published: (2024)
by: Mane, Tejas, et al.
Published: (2024)
HETHUB: A Distributed Training System with Heterogeneous Cluster for Large-Scale Models
by: Xu, Si, et al.
Published: (2024)
by: Xu, Si, et al.
Published: (2024)
AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices
by: Lin, Zheng, et al.
Published: (2024)
by: Lin, Zheng, et al.
Published: (2024)
Harpagon: Minimizing DNN Serving Cost via Efficient Dispatching, Scheduling and Splitting
by: Zhao, Zhixin, et al.
Published: (2024)
by: Zhao, Zhixin, et al.
Published: (2024)
Heta: Distributed Training of Heterogeneous Graph Neural Networks
by: Zhong, Yuchen, et al.
Published: (2024)
by: Zhong, Yuchen, et al.
Published: (2024)
Addressing Variable Heterogeneity in Distributed Multimodal Training with Entrain
by: Jang, Insu, et al.
Published: (2026)
by: Jang, Insu, et al.
Published: (2026)
Augur: Pre-Execution Energy Prediction for Workflow Tasks in Heterogeneous Clusters
by: West, Kathleen, et al.
Published: (2026)
by: West, Kathleen, et al.
Published: (2026)
Similar Items
-
Aladdin: Joint Placement and Scaling for SLO-Aware LLM Serving
by: Nie, Chengyi, et al.
Published: (2024) -
Poplar: Efficient Scaling of Distributed DNN Training on Heterogeneous GPU Clusters
by: Zhang, WenZheng, et al.
Published: (2024) -
HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis
by: Zhang, Shiwei, et al.
Published: (2024) -
HexiScale: Facilitating Large Language Model Training over Heterogeneous Hardware
by: Yan, Ran, et al.
Published: (2024) -
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators
by: K., Prashanthi S., et al.
Published: (2023)