Hi, thanks! I use vllm to inference the llama-7B model on single gpu, and tensor-parallel on 2-gpus and 4-gpus, we found that it is 10 times faster than HF on a single GPU, but using tensor parallelism, there is no significant increase i...
data_parallelism) Create Experiment, including hooks Create Estimator T2TModel.estimator_model_fn model(features) model.model_fn model.bottom model.body model.top model.loss [TRAIN] model.estimator_spec_train train_op = model.optimize [EVAL] model.estimator_spec_eval Create metrics Create...
分布式机器学习中的数据并行(Data Parallelism)和模型并行(model parallelism) 前言: 现在的模型越来越复杂,参数越来越多,其训练集也在剧增。在一个很大的数据集集中训练一个比较复杂的模型往往需要多个GPU。现在比较常见的并行策略有:数据并行和模型并行,本文主要讨论这两个并行策略。 数据并行(Data Parallelism): 在现...
transformerllamadistributed-trainingfine-tuningpre-trainingtensor-parallelismllminstruction-tuningllm-trainingllm-finetuningphi-3 UpdatedMar 11, 2025 Python Fast and easy distributed model training examples. deep-learningpytorchzerodata-parallelismmodel-parallelismdistributed-trainingxlatensor-parallelismllmfsdpsequence...
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)...
Both handle parallelism — but in different ways. CUDA Cores vs Tensor Cores: Side-by-Side Comparison Feature CUDA Cores Tensor Cores Primary Role General-purpose parallel processing Deep learning acceleration Architecture Purpose Built for a wide range of tasks (compute, graphics, simulations) ...
(i.e., nested). DNNs are then defined by high-order compute operators like map/reduce/scan and data access operators like window/stride on FractalTensor. This new way of DNN definition explicitly exposes nested data parallelism and fine-grained data access ...
在合理的 batching 后可以利用好 tensor core；attention 是batched gemv，batching 只能增加 parallelism...
Uncover Nested Data Parallelism and Data Reuse in DNN Computation with FractalTensorYing Cao , Fan Yang , Mao Yang September 2024Download BibTex Abstract to come… Opens in a new tab Research Areas Programming languages and software engineering Systems and...
Is a medium or large size and requires larger batch sizes for training during which high parallelism is beneficial. TPU The TPU is much closer to an ASIC, providing a limited number of math functions, primarily matrix processing, expressly intended for ML tasks. A TPU is noted for high throu...