CFP: Efficient Optimization of Intra-Operator Parallelism Plans for Large Model Training
Fuente:
arXiv
Saved in:
| Main Authors: | Hu, Weifang, Shi, Xuanhua, Zhang, Yunkai, Wu, Chang, Peng, Xuan, Zhai, Jiaqi, Jin, Hai, Qian, Xuehai, Xue, Jingling, Zhou, Yongluan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DawnPiper: A Memory-scablable Pipeline Parallel Training Framework
by: Peng, Xuan, et al.
Published: (2025)
by: Peng, Xuan, et al.
Published: (2025)
Redox: Improving I/O Efficiency of Model Training Through File Redirection
by: Li, Yuhao, et al.
Published: (2025)
by: Li, Yuhao, et al.
Published: (2025)
A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training
by: Jiang, Lijuan, et al.
Published: (2025)
by: Jiang, Lijuan, et al.
Published: (2025)
gECC: A GPU-based high-throughput framework for Elliptic Curve Cryptography
by: Xiong, Qian, et al.
Published: (2024)
by: Xiong, Qian, et al.
Published: (2024)
DynaFlow: Transparent and Flexible Intra-Device Parallelism via Programmable Operator Scheduling
by: Pan, Yi, et al.
Published: (2026)
by: Pan, Yi, et al.
Published: (2026)
UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training
by: Zheng, Size, et al.
Published: (2026)
by: Zheng, Size, et al.
Published: (2026)
CaPGNN: Optimizing Parallel Graph Neural Network Training with Joint Caching and Resource-Aware Graph Partitioning
by: Song, Xianfeng, et al.
Published: (2025)
by: Song, Xianfeng, et al.
Published: (2025)
LoongTrain: Efficient Training of Long-Sequence LLMs with Head-Context Parallelism
by: Gu, Diandian, et al.
Published: (2024)
by: Gu, Diandian, et al.
Published: (2024)
Prefill-Decode Aggregation or Disaggregation? Unifying Both for Goodput-Optimized LLM Serving
by: Wang, Chao, et al.
Published: (2025)
by: Wang, Chao, et al.
Published: (2025)
Seq1F1B: Efficient Sequence-Level Pipeline Parallelism for Large Language Model Training
by: Sun, Ao, et al.
Published: (2024)
by: Sun, Ao, et al.
Published: (2024)
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials
by: Wang, Hongyu, et al.
Published: (2026)
by: Wang, Hongyu, et al.
Published: (2026)
Bandwidth-Aware and Cost-Efficient Pipeline Parallel Scheduling in Geo-Distributed LLM Training
by: Zhang, Han, et al.
Published: (2026)
by: Zhang, Han, et al.
Published: (2026)
HARP: Orchestrating Automated Parallel Training on Heterogeneous GPU Clusters
by: Liang, Antian, et al.
Published: (2025)
by: Liang, Antian, et al.
Published: (2025)
Amoeba: Runtime Tensor Parallel Transformation for LLM Inference Services
by: Chen, Haoyu, et al.
Published: (2025)
by: Chen, Haoyu, et al.
Published: (2025)
Fault-Tolerant Hybrid-Parallel Training at Scale with Reliable and Efficient In-memory Checkpointing
by: Wang, Yuxin, et al.
Published: (2023)
by: Wang, Yuxin, et al.
Published: (2023)
Heimdall++: Optimizing GPU Utilization and Pipeline Parallelism for Efficient Single-Pulse Detection
by: Xia, Bingzheng, et al.
Published: (2025)
by: Xia, Bingzheng, et al.
Published: (2025)
Hecate: Unlocking Efficient Sparse Model Training via Fully Sharded Sparse Data Parallelism
by: Qing, Yuhao, et al.
Published: (2025)
by: Qing, Yuhao, et al.
Published: (2025)
SPPO:Efficient Long-sequence LLM Training via Adaptive Sequence Pipeline Parallel Offloading
by: Chen, Qiaoling, et al.
Published: (2025)
by: Chen, Qiaoling, 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)
by: Dutta, Ankita, et al.
Published: (2025)
Zeppelin: Balancing Variable-length Workloads in Data Parallel Large Model Training
by: Chen, Chang, et al.
Published: (2025)
by: Chen, Chang, et al.
Published: (2025)
Tetris: Efficient Intra-Datacenter Calls Packing for Large Conferencing Services
by: Gandhi, Rohan, et al.
Published: (2025)
by: Gandhi, Rohan, et al.
Published: (2025)
StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training
by: Liu, Ziming, et al.
Published: (2024)
by: Liu, Ziming, 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)
ZeroPP: Unleashing Exceptional Parallelism Efficiency through Tensor-Parallelism-Free Methodology
by: Tang, Ding, et al.
Published: (2024)
by: Tang, Ding, et al.
Published: (2024)
InternEvo: Efficient Long-sequence Large Language Model Training via Hybrid Parallelism and Redundant Sharding
by: Chen, Qiaoling, et al.
Published: (2024)
by: Chen, Qiaoling, et al.
Published: (2024)
Oases: Efficient Large-Scale Model Training on Commodity Servers via Overlapped and Automated Tensor Model Parallelism
by: Li, Shengwei, et al.
Published: (2023)
by: Li, Shengwei, et al.
Published: (2023)
GRNND: A GPU-Parallel Relative NN-Descent Algorithm for Efficient Approximate Nearest Neighbor Graph Construction
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Optimizing Long-context LLM Serving via Fine-grained Sequence Parallelism
by: Li, Cong, et al.
Published: (2025)
by: Li, Cong, et al.
Published: (2025)
Pro-Prophet: A Systematic Load Balancing Method for Efficient Parallel Training of Large-scale MoE Models
by: Wang, Wei, et al.
Published: (2024)
by: Wang, Wei, et al.
Published: (2024)
Parallelized Multi-Agent Bayesian Optimization in Lava
by: Snyder, Shay, et al.
Published: (2024)
by: Snyder, Shay, et al.
Published: (2024)
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)
Adaptra: Straggler-Resilient Hybrid-Parallel Training with Pipeline Adaptation
by: Wu, Tianyuan, et al.
Published: (2025)
by: Wu, Tianyuan, et al.
Published: (2025)
DreamDDP: Accelerating Data Parallel Distributed LLM Training with Layer-wise Scheduled Partial Synchronization
by: Tang, Zhenheng, et al.
Published: (2025)
by: Tang, Zhenheng, et al.
Published: (2025)
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)
Performance-Driven Optimization of Parallel Breadth-First Search
by: Bhaskar, Marati, et al.
Published: (2025)
by: Bhaskar, Marati, et al.
Published: (2025)
ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism
by: Ma, Tenghui, et al.
Published: (2026)
by: Ma, Tenghui, et al.
Published: (2026)
ElasWave: An Elastic-Native System for Scalable Hybrid-Parallel Training
by: Kang, Xueze, et al.
Published: (2025)
by: Kang, Xueze, et al.
Published: (2025)
PaSE: Parallelization Strategies for Efficient DNN Training
by: Elango, Venmugil
Published: (2024)
by: Elango, Venmugil
Published: (2024)
ServeGen: Workload Characterization and Generation of Large Language Model Serving in Production
by: Xiang, Yuxing, et al.
Published: (2025)
by: Xiang, Yuxing, et al.
Published: (2025)
Mesh-Attention: A New Communication-Efficient Distributed Attention with Improved Data Locality
by: Chen, Sirui, et al.
Published: (2025)
by: Chen, Sirui, et al.
Published: (2025)
Similar Items
-
DawnPiper: A Memory-scablable Pipeline Parallel Training Framework
by: Peng, Xuan, et al.
Published: (2025) -
Redox: Improving I/O Efficiency of Model Training Through File Redirection
by: Li, Yuhao, et al.
Published: (2025) -
A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training
by: Jiang, Lijuan, et al.
Published: (2025) -
gECC: A GPU-based high-throughput framework for Elliptic Curve Cryptography
by: Xiong, Qian, et al.
Published: (2024) -
DynaFlow: Transparent and Flexible Intra-Device Parallelism via Programmable Operator Scheduling
by: Pan, Yi, et al.
Published: (2026)