Megatron-LM 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。 torch.distributed(dist) 为运行...
2024/02/26 Update:tensor parallel 在主流的推理框架已经很好的支持了, vLLM 和 lightllm 都是很好的选择。现在 tensor-parallel 这个项目的意义主要在做一些实验上,真实场景下不再适用。 上一篇文章中我用 Al…
Slicing a PyTorch Tensor Into Parallel Shards pytorchmodel-parallelismtensor-parallelism UpdatedJul 27, 2021 Python ai-decentralized/BloomBee Star90 Code Issues Pull requests Decentralized LLMs fine-tuning and inference with offloading distributed-systemsmachine-learningdeep-learningpytorchllamapipeline-parallelis...
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...
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) Optimized for matrix-heavy operations in AI/ML Best...
scalability有限,详细地,我们在给Tensor Core准备数据的时候,需要warp内所有线程协调地考虑加载一部分矩阵数据,每一个线程都要算得自己独立的矩阵块的一部分地址,再加上为了隐藏数据加载的延时,全局内存到共享内存,共享内存到寄存器的数据加载都会构建多层级的软流水(software pipeline),消耗了很多寄存器及存储带宽;可扩展...
faster and with far lower power consumption than more traditional processor types. In short, a TPU takes input data, breaks down the data into multiple tasks calledvectors, performs multiplication and addition on each vector simultaneously and in parallel, and then delivers the output to the ML ...
The scale of a parallel computer — the maximum number of processing elements in the system — is in a very practical sense limited by the reliability of the system. The TSP processing elements use a deterministic datapath and error correction of all single-bit erro...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Specifying device_id in init_process_group causes tensor parallel + pipeline parallel to fail · pytorch/pytorch@d765077
在《Parallel Thread Execution ISA》中,9.7.13.3节和9.7.13.4节分别给出了两种指令:wmma指令和mma指令,个人感觉这两类指令可以说是非常类似,其中wmma指令更像是Volta架构的遗留产物。 wmma指令包括: // wmma.loadwmma.load.a.sync.aligned.layout.shape{.ss}.atyper,[p]{,stride};wmma.load.b.sync.aligned....