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Model Parallelism With Subnetwork Data Parallelism
Arxiv
0+阅读 · 10月2日
Model Parallelism With Subnetwork Data Parallelism
Arxiv
0+阅读 · 10月1日
Zeppelin: Balancing Variable-length Workloads in Data Parallel Large Model Training
Arxiv
0+阅读 · 9月29日
Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems
Arxiv
0+阅读 · 6月21日
Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems
Arxiv
0+阅读 · 6月24日
Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training
Arxiv
0+阅读 · 4月25日
Characterization of GPU TEE Overheads in Distributed Data Parallel ML Training
Arxiv
0+阅读 · 3月27日
Efficient allocation of image recognition and LLM tasks on multi-GPU system
Arxiv
0+阅读 · 3月19日
DeFT: Mitigating Data Dependencies for Flexible Communication Scheduling in Distributed Training
Arxiv
0+阅读 · 3月21日
Efficient Long Context Fine-tuning with Chunk Flow
Arxiv
0+阅读 · 3月4日
Efficient Long Context Fine-tuning with Chunk Flow
Arxiv
0+阅读 · 3月6日
ByteScale: Efficient Scaling of LLM Training with a 2048K Context Length on More Than 12,000 GPUs
Arxiv
0+阅读 · 2月28日
FlexDeMo: Decoupled Momentum Optimization for Hybrid Sharded Data Parallel Training
Arxiv
0+阅读 · 3月18日
A Benchmarking Platform for DDR4 Memory Performance in Data-Center-Class FPGAs
Arxiv
0+阅读 · 1月26日
Hecate: Unlocking Efficient Sparse Model Training via Fully Sharded Sparse Data Parallelism
Arxiv
0+阅读 · 2月4日
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