Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Haowei, Tian, Yu, Yang, Zhongheng, Wang, Zhao, Zhou, Chengrui, Li, Dannier |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can Large Language Models Write Parallel Code?
by: Nichols, Daniel, et al.
Published: (2024)
by: Nichols, Daniel, et al.
Published: (2024)
HPC-Coder: Modeling Parallel Programs using Large Language Models
by: Nichols, Daniel, et al.
Published: (2023)
by: Nichols, Daniel, et al.
Published: (2023)
Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization
by: Zhu, Zhanda, et al.
Published: (2025)
by: Zhu, Zhanda, et al.
Published: (2025)
Can Large Language Models Predict Parallel Code Performance?
by: Bolet, Gregory, et al.
Published: (2025)
by: Bolet, Gregory, et al.
Published: (2025)
DWDP: Distributed Weight Data Parallelism for High-Performance LLM Inference on NVL72
by: Li, Wanqian, et al.
Published: (2026)
by: Li, Wanqian, et al.
Published: (2026)
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection
by: Barron, Ryan, et al.
Published: (2024)
by: Barron, Ryan, et al.
Published: (2024)
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism
by: Chen, Yanxi, et al.
Published: (2023)
by: Chen, Yanxi, et al.
Published: (2023)
SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models
by: Kim, Han-Byul, et al.
Published: (2025)
by: Kim, Han-Byul, et al.
Published: (2025)
BitPipe: Bidirectional Interleaved Pipeline Parallelism for Accelerating Large Models Training
by: Wu, Houming, et al.
Published: (2024)
by: Wu, Houming, et al.
Published: (2024)
AdaPtis: Reducing Pipeline Bubbles with Adaptive Pipeline Parallelism on Heterogeneous Models
by: Guo, Jihu, et al.
Published: (2025)
by: Guo, Jihu, et al.
Published: (2025)
SimpleFSDP: Simpler Fully Sharded Data Parallel with torch.compile
by: Zhang, Ruisi, et al.
Published: (2024)
by: Zhang, Ruisi, et al.
Published: (2024)
Training Through Failure: Effects of Data Consistency in Parallel Machine Learning Training
by: Cao, Ray, et al.
Published: (2024)
by: Cao, Ray, et al.
Published: (2024)
TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training
by: Liu, Man, et al.
Published: (2026)
by: Liu, Man, et al.
Published: (2026)
Opara: Exploiting Operator Parallelism for Expediting DNN Inference on GPUs
by: Chen, Aodong, et al.
Published: (2023)
by: Chen, Aodong, et al.
Published: (2023)
FreeRide: Harvesting Bubbles in Pipeline Parallelism
by: Zhang, Jiashu, et al.
Published: (2024)
by: Zhang, Jiashu, et al.
Published: (2024)
High-Performance Parallel Optimization of the Fish School Behaviour on the Setonix Platform Using OpenMP
by: Wang, Haitian, et al.
Published: (2025)
by: Wang, Haitian, et al.
Published: (2025)
CCL-D: A High-Precision Diagnostic System for Slow and Hang Anomalies in Large-Scale Model Training
by: Gu, Yida, et al.
Published: (2026)
by: Gu, Yida, et al.
Published: (2026)
EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models
by: Cheng, Jialiang, et al.
Published: (2024)
by: Cheng, Jialiang, et al.
Published: (2024)
Rethinking Dynamic Networks and Heterogeneous Computing with Automatic Parallelization
by: Wu, Ruilong, et al.
Published: (2025)
by: Wu, Ruilong, et al.
Published: (2025)
Collaborative Split Federated Learning with Parallel Training and Aggregation
by: Papageorgiou, Yiannis, et al.
Published: (2025)
by: Papageorgiou, Yiannis, et al.
Published: (2025)
SPECTRE: Hybrid Ordinary-Parallel Speculative Serving for Resource-Efficient LLM Inference
by: Xie, Jincheng, et al.
Published: (2026)
by: Xie, Jincheng, et al.
Published: (2026)
Training Overhead Ratio: A Practical Reliability Metric for Large Language Model Training Systems
by: Lu, Ning, et al.
Published: (2024)
by: Lu, Ning, et al.
Published: (2024)
Accelerating Long-Tail Generation in Synchronous RLHF Training via Adaptive Tensor Parallelism
by: Zhao, Long, et al.
Published: (2026)
by: Zhao, Long, et al.
Published: (2026)
TimelyFreeze: Adaptive Parameter Freezing Mechanism for Pipeline Parallelism
by: Cho, Seonghye, et al.
Published: (2026)
by: Cho, Seonghye, et al.
Published: (2026)
HeteGen: Heterogeneous Parallel Inference for Large Language Models on Resource-Constrained Devices
by: Zhao, Xuanlei, et al.
Published: (2024)
by: Zhao, Xuanlei, et al.
Published: (2024)
Helix Parallelism: Rethinking Sharding Strategies for Interactive Multi-Million-Token LLM Decoding
by: Bhatia, Nidhi, et al.
Published: (2025)
by: Bhatia, Nidhi, et al.
Published: (2025)
Context Parallelism for Scalable Million-Token Inference
by: Yang, Amy, et al.
Published: (2024)
by: Yang, Amy, et al.
Published: (2024)
Para-B&B: Load-Balanced Deterministic Parallelization of Solving MIP
by: Zhang, Jinyu, et al.
Published: (2026)
by: Zhang, Jinyu, et al.
Published: (2026)
Dora: QoE-Aware Hybrid Parallelism for Distributed Edge AI
by: Jin, Jianli, et al.
Published: (2025)
by: Jin, Jianli, et al.
Published: (2025)
Federated Fine-Tuning of Sparsely-Activated Large Language Models on Resource-Constrained Devices
by: Chen, Fahao, et al.
Published: (2025)
by: Chen, Fahao, et al.
Published: (2025)
Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization
by: Li, Haoyang, et al.
Published: (2024)
by: Li, Haoyang, et al.
Published: (2024)
OrchMLLM: Orchestrate Multimodal Data with Batch Post-Balancing to Accelerate Multimodal Large Language Model Training
by: Zheng, Yijie, et al.
Published: (2025)
by: Zheng, Yijie, et al.
Published: (2025)
Adaptive Fault Tolerance Mechanisms of Large Language Models in Cloud Computing Environments
by: Jin, Yihong, et al.
Published: (2025)
by: Jin, Yihong, et al.
Published: (2025)
Cloud-Based AI Systems: Leveraging Large Language Models for Intelligent Fault Detection and Autonomous Self-Healing
by: Ji, Cheng, et al.
Published: (2025)
by: Ji, Cheng, et al.
Published: (2025)
Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling
by: Li, Yan, et al.
Published: (2025)
by: Li, Yan, et al.
Published: (2025)
xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism
by: Fang, Jiarui, et al.
Published: (2024)
by: Fang, Jiarui, et al.
Published: (2024)
Efficient MoE Inference with Fine-Grained Scheduling of Disaggregated Expert Parallelism
by: Pan, Xinglin, et al.
Published: (2025)
by: Pan, Xinglin, et al.
Published: (2025)
Using Sequential Runtime Distributions for the Parallel Speedup Prediction of SAT Local Search
by: Arbelaez, Alejandro, et al.
Published: (2024)
by: Arbelaez, Alejandro, et al.
Published: (2024)
Astra: Efficient and Money-saving Automatic Parallel Strategies Search on Heterogeneous GPUs
by: Wang, Peiran, et al.
Published: (2025)
by: Wang, Peiran, et al.
Published: (2025)
Online Parallel Multi-Task Relationship Learning via Alternating Direction Method of Multipliers
by: Li, Ruiyu, et al.
Published: (2024)
by: Li, Ruiyu, et al.
Published: (2024)
Similar Items
-
Can Large Language Models Write Parallel Code?
by: Nichols, Daniel, et al.
Published: (2024) -
HPC-Coder: Modeling Parallel Programs using Large Language Models
by: Nichols, Daniel, et al.
Published: (2023) -
Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization
by: Zhu, Zhanda, et al.
Published: (2025) -
Can Large Language Models Predict Parallel Code Performance?
by: Bolet, Gregory, et al.
Published: (2025) -
DWDP: Distributed Weight Data Parallelism for High-Performance LLM Inference on NVL72
by: Li, Wanqian, et al.
Published: (2026)