它支持多种并行策略,包括张量并行(Tensor Parallelism)、流水线并行(Pipeline Parallelism)和数据并行(Data Parallelism)。DeepSpeed 的 ZeRO 优化器通过零冗余设计显著减少了内存占用,同时支持混合精度训练。 2.Megatron-LM Megatron-LM 是 NVIDIA 推出的分布式训练框架,专为训练超大规模语言模型设计。它在张量并行方面表现...
Megatron-LM 综合应用了数据并行(Data Parallelism),张量并行(Tensor Parallelism)和流水线并行(Pipeline Parallelism)。很多大模型的训练过程都采用它,例如bloom、opt、智源等。 torch.distributed(dist) 为运行在一台或多台机器上的多个计算节点之间的PyTorch 提供支持多进程并行性通信的原语。他能轻松地并行化在跨进程...
MegatronLM的第一篇论文【Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism】是2020年出的,针对billion级别的模型进行训练,例如具有38亿参数的类GPT-2的transformer模型和具有39亿参数的BERT模型。 分布式训练的模型并行有两种方式,一种是层间并行(inter-layer),也就是Pipeline流水...
Tensor parallelism takes place at the level ofnn.Modules; it partitions specific modules in the model across tensor parallel ranks. This is in addition to the existing partition of theset of modulesused in pipeline parallelism. When a module is partitioned through tensor parallelism, its for...
distributed-systemsmachine-learningdeep-learningpytorchllamapipeline-parallelismtensor-parallelism UpdatedMar 14, 2025 Python Large scale 4D parallelism pre-training for 🤗 transformers in Mixture of Experts *(still work in progress)* transformersmoedata-parallelismdistributed-optimizersmodel-parallelismmegatronmi...
I am training the LLM with DeepSpeed Pipeline Parallel (ZeRO0 or ZeRO1 used). But I have a tricky issue: Assuming global_batch_size=4, single machine with 8GPUS, and PP=8, so DP=1, and micro_batch_size=4. Further assuming the first batch contains the input sequence with shape (4,...
on 8 GPUs from 10mn with regular PyTorch weights down to 45s. This really speeds up feedbacks loops when developing on the model. For instance you don't have to have separate copies of the weights when changing the distribution strategy (for instance Pipeline Parallelism vs Tensor Parallelism)...
tensor parallelism Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism 张量并行,模型并行的一种,是把模型同一层之间纵向切割,将参数分割到不同的GPU上去计算。比如说pipeline是把self attention和feed forward切开分别训练,那tensor就是把self attention那一层的多个注意力头切开去分别...
Inside TensorFlow: tf.data - TF Input Pipeline High-Level APIs in TensorFlow 2.0 (TensorFlow Meet AI for Mobile and IoT Devices: TensorFlow Lite (Go TensorFlow Extended: Machine Learning Pipelines an Cutting Edge TensorFlow: New Techniques (Google I/视频...
张量并行(TP,Tensor Parallelism)可以将模型的张量(如权重矩阵)分割到多个 GPU 上进行并行计算,以加速模型的推理过程,特别是对于单个 GPU 上无法放下整个模型的情形。本文是作者在初读vllm源码的过程中对tp…