multi-gpu

The Forge Cross-Platform Rendering Framework PC Windows, Linux, Ray Tracing, macOS / iOS, Android, XBOX, PS4, PS5, Switch, Quest 2

Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP

Face recognition system for ID photos

Extract video features from raw videos using multiple GPUs. We support RAFT and PWC flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, ResNet features.

Multi-threaded GUI manager for mass creation of AI-generated art with support for multiple GPUs.

QUDA is a library for performing calculations in lattice QCD on GPUs.

GPU-ready Dockerfile to run Stability.AI stable-diffusion model v2 with a simple web interface. Includes multi-GPUs support.

Package for writing high-level code for parallel high-performance stencil computations that can be deployed on both GPUs and CPUs

Code for training py-faster-rcnn and py-R-FCN on multiple GPUs in caffe

A PyTorch implementation of the 'FaceNet' paper for training a facial recognition model with Triplet Loss using the glint360k dataset. A pre-trained model using Triplet Loss is available for download.

multi-gpu pre-training in one machine for BERT from scratch without horovod (Data Parallelism)

The world's first CUDA implementation of Weakly-Compressible Smoothed Particle Hydrodynamics

Almost trivial distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid

Multi-device OpenCL kernel load balancer and pipeliner API for C#. Uses shared-distributed memory model to keep GPUs updated fast while using same kernel on all devices(for simplicity).

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

Efficient Distributed GPU Programming for Exascale, an SC/ISC Tutorial

Neutron: A pytorch based implementation of Transformer and its variants.

Multi-GPU training for Keras

Co-attending Regions and Detections for VQA.

GPU Framework for Radio Astronomical Image Synthesis