模型：GPT-13BMegatron：v2.4，tensor-model-parallel-size 设置为 4, pipeline-model-parallel-size 设置为 4DeepSpeed：v0.4.2，使用 DeepSpeedExamples 开源社区中默认的 zero3 的配置运行环境V100/TCP ：100Gb/s TCP 网络带宽，4 机，每机 8 张 Tesla V100 32G GPUV100/RDMA：100Gb/s RDMA 网络带宽，...
因为现在的large scale learning系统在工业界的应用，我觉得还更多是一种以embarrassingly parallel为代表的...
classPipelineParallelResNet50(ModelParallelResNet50):def__init__(self,split_size=20,*args,**kwargs):super(
{ "type": "gpt3", "world_size": 1, "model_parallel_size": 1, "checkpoint_model_parallel_size": 1, "rank": 0 }, "pipeline": { "type": "gpt3-generation" }, "train": { "work_dir": "/tmp", "max_epochs": 3, "dataloader": { "batch_size_per_gpu": 4, "workers_per_...
2, 是带来了流水线优化，提升了计算效率。但是也有缺点，比如水平划分模型时，中间的某一层计算需要上一...
为了加速训练过程和提高模型的准确性,可以采用模型并行处理(Model Parallel Processing)的方法。模型并行处理是一种将模型分散到多个GPU或CPU上进行计算的技术,可以实现并行计算,提高计算效率和模型训练速度。模型并行处理的基本原理是将一个完整的模型分成若干个子模型,每个子模型可以运行在不同的设备上。这样,输入数据...
相比于data-parallel和model-parallel,提出了更多维度的split方案。SOAP(sample,operator,atrribute,param)这四个维度的split方案。 在四个维度之上,提出了一种在候选空间搜索的方案 提出了一个更加轻量的simulator,可以更快速的对proposed split strategy做evaluate。相比直接执行的方案提升了3个数量级。
Merge the model tomodel_parallel_size=1: (replace the 4 below with your trainingMP_SIZE) torchrun --standalone --nnodes=1 --nproc-per-node=4 utils/merge_model.py --version base --bf16 --from_pretrained ./checkpoints/merged_lora_(cogagent/cogvlm490/cogvlm224) ...
As we increased the number of pipeline stages, we also increased the size of the model by proportionally increasing the number of layers in the model. For example, with a pipeline-parallel size of 1, we used a model with three transformer layers and ~15 billion parameters. With a pipeline...
The survey design for the parallel model2.2. Sample size formulae based on the power analysis method2.2.1. The one-sided test2.2.2. The two-sided test3. Evaluation of performance3.1. Comparison of the asymptotic power with the exact power3.2. Comparison with the design of direct questioning ...