MobileNet build with Tensorflow

Gradually-Warmup Learning Rate Scheduler for PyTorch

AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Open-source tools for training and evaluating Vision Language Models for OCR

code for py-R-FCN-multiGPU maintained by bupt-priv

TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software

CRNN(Convolutional Recurrent Neural Network), with optional STN(Spatial Transformer Network), in Tensorflow, multi-gpu supported.

OpenGL sample for the new GL_NVX_linked_gpu_multicast extension

ide-cap-chan is a utility for batch image captioning with natural language using various VL models

Custom Iterable Dataset Class for Large-Scale Data Loading

A modular, multilingual, and multimodal Retrieval-Augmented Generation (RAG) system tailored for the financial analysis of Public Investment Fund (PIF) annual reports.

multi_gpu_infer 多gpu预测 multiprocessing or subprocessing

⚡ LLaMA-2 model experiment

This helps you to submit job with multinode & multgpu in Slurm in Torchrun

Python interface to the NVIDIA CublasXt API

Recommendation Engine powered by Matrix Factorization.

Keras light-weight model for sketch images classification using Quick!Draw dataset

Remote Multi-GPU Path Tracer built with C++ and CUDA.

A comprehensive benchmarking and profiling tool designed for JAX in HPC environments, offering automated instrumentation, strong/weak scaling analysis, and performance visualization.

Efficient multi-GPU OCR inference framework leveraging parallel processes for accelerated token throughput and faster batch processing. Designed for scalable, high-performance optical character recognition workloads using PyTorch. Supports dynamic GPU assignment, optimized resource utilization, and easy integration for large-scale image datasets.

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Implementations of some popular approaches for efficient deep learning training and inference

Distributed_compy is a distributed computing library that offers multi-threading, heterogeneous (CPU + mult-GPU), and multi-node support

Leveraging Structural Indexes for High-Performance JSON Data Processing on GPUs

🚀 Run efficient DeepSeek-OCR inference with Python scripts, supporting both single and multi-GPU setups for versatile performance on various hardware.

Training Using Multiple GPUs

A lightweight, pytorch-based NN training platform

Very minimal pytorch boilerplate with wandb logging and multi gpu support