Tensor并行(Tensor Parallelism,TP)是模型并行(Model Parallelism,MP)中的一种技术,通过对Tensor(张量)的拆分,将原本在单个设备上的一次Tensor计算拆分到多台设备上进行并行计算,然后将计算结果合并为目标张量。这种并行方式能够显著提高大规模深度学习模型的训练效率,尤其是在模型参数达到数十亿甚至数百亿级别时。 2. ...
实现Tensor parallelism 的前提是计算设备需要处于互联状态,如上图所示,以GPU为例,因产品形态不同,有全连接和部分连接两种状态。 2. GPT 的 tensor parallelism 方案 下图是一个典型GPT模型的结构,主要包括:Embeddings, Decoder(n layers, self-attention+MLP), language model(LM)。下面将逐个部分讨论 tensor parall...
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...
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 is a type of model parallelism in which specific model weights, gradients, and optimizer states are split across devices.
Tensor Parallelism with JAX + Shard Map transformersgpttpujaxtensor-parallelismpjitshmap UpdatedSep 29, 2023 Python Improve this page Add a description, image, and links to thetensor-parallelismtopic page so that developers can more easily learn about it. ...
Tensor parallelism is a type of model parallelism in which specific model weights, gradients, and optimizer states are split across devices.
NVIDIA Megatron-LM 是一个基于 PyTorch 的分布式训练框架,用来训练基于Transformer的大型语言模型。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。
llama model with more than one gpu by setting tensor_parallel_size=2. The model won't load. It works fine with on a single instance when I don't use a ray cluster. I cannot only set tensor_parallel_size=1 on ray cluster. Is there a way to use tensor parallelism on a ray cluster...
近期要开始大模型方面的工作,megatron自然是绕不开的一环,本文是对《Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism》的阅读记录,写的很随意,不喜勿喷。 transformer based模型的MLP子模块为: MLP -> GELU -> MLP -> Dropout,写成公式如下所示: Z=Dropout(GeLU(XA)B)...