A bidirectional pipeline parallelism algorithm for computation-communication overlap in DeepSeek V3/R1 training.
Las características principales de deepseek-ai/dualpipe son: Attention Optimization, Distributed Training Tools.
Las alternativas de código abierto para deepseek-ai/dualpipe incluyen: deepseek-ai/eplb — Expert Parallelism Load Balancer. deepseek-ai/deepep — DeepEP is a distributed model accelerator and expert-parallel communication library designed to optimize the training… open-mmlab/openpcdet — OpenPCDet is a PyTorch deep learning library and toolbox for LiDAR 3D object detection. It functions as a point cloud… stability-ai/stablelm — StableLM is a pre-trained transformer-based large language model designed for natural language generation and… deepseek-ai/deepgemm — DeepGEMM is a suite of specialized GPU kernels and a just-in-time compiler designed for low-precision matrix… dao-ailab/flash-attention — FlashAttention is an attention mechanism optimization library and machine learning acceleration framework designed to…
DeepEP is a distributed model accelerator and expert-parallel communication library designed to optimize the training and inference of large-scale neural networks. It provides specialized GPU communication kernels and a remote GPU memory interface to facilitate high-throughput data exchange between hardware nodes. The system utilizes dynamic kernel generation to compile optimized GPU kernels during execution, removing the need for separate installation compilation steps. It implements virtual-lane traffic isolation to prevent interference between different data streams and employs routing met
OpenPCDet is a PyTorch deep learning library and toolbox for LiDAR 3D object detection. It functions as a point cloud processing framework designed to develop, train, and evaluate machine learning models that identify and locate objects in three dimensional space. The project includes a GPU-accelerated geometry engine for high-performance implementation of 3D intersection over union and rotated non-maximum suppression. It also provides a distributed model training tool to scale the training and testing of detection models across multiple GPUs and computing nodes. The framework covers point c
StableLM is a pre-trained transformer-based large language model designed for natural language generation and zero-shot inference. It functions as a causal language model that predicts the next token in a sequence to produce human-like text for conversational and creative writing tasks. The model is built as a fine-tunable base, allowing the adaptation of pre-trained weights to specific tasks or styles through custom dataset training and weight regularization. It utilizes rotary positional embeddings and flash-attention to optimize memory usage and processing efficiency during deployment on G