Datasets:
Tasks:
Tabular Regression
Formats:
csv
Size:
< 1K
Tags:
large-language-models
distributed-training
performance-modeling
profiling
mindspeed-llm
ascend
License:
Update README.md
Browse files
README.md
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Each model is sampled under feasible combinations of data parallelism (DP), tensor parallelism (TP), pipeline parallelism (PP), context parallelism (CP), expert parallelism (EP, for MoE models), and recomputation settings. The released files contain structured CSV records for iteration time, rank-level peak memory, operator latency, communication behavior, and matrix-operator hardware characteristics.
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The original raw dataset is available at [anonymous-
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This dataset is ready for research use. Commercial use should follow the license and terms below.
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## Reference(s)
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- [MindSpeed-LLM](https://gitcode.com/Ascend/MindSpeed-LLM)
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- [anonymous-
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## Ethical Considerations
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Each model is sampled under feasible combinations of data parallelism (DP), tensor parallelism (TP), pipeline parallelism (PP), context parallelism (CP), expert parallelism (EP, for MoE models), and recomputation settings. The released files contain structured CSV records for iteration time, rank-level peak memory, operator latency, communication behavior, and matrix-operator hardware characteristics.
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The original raw dataset is available at [anonymous-ljasd/LM-SimBench_raw](https://huggingface.co/datasets/anonymous-ljasd/LM-SimBench_raw). This repository publishes the organized CSV dataset for downstream performance modeling and analysis.
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This dataset is ready for research use. Commercial use should follow the license and terms below.
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## Reference(s)
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- [MindSpeed-LLM](https://gitcode.com/Ascend/MindSpeed-LLM)
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- [anonymous-ljasd/LM-SimBench_raw](https://huggingface.co/datasets/anonymous-ljasd/LM-SimBench_raw)
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## Ethical Considerations
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