High-level C++ for Accelerator Clusters

Distributed tensors and Machine Learning framework with GPU and MPI acceleration in Python

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

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

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

GPU Framework for Radio Astronomical Image Synthesis

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

Chains stable-diffusion-webui instances together to facilitate faster image generation.

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

A dual-GPU DEM solver with complex grain geometry support

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

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

POT3D: High Performance Potential Field Solver

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

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

Hands-on workshop CUDA-Q NVIDIA in RWTH Aachen University & Technische Universität Berlin, June 2024.

Multi-GPU & CPU OpenCL kernel executor with load-balancing as if there is one big GPU.

Source code for the CPU-Free model - a fully autonomous execution model for multi-GPU applications that completely excludes the involvement of the CPU beyond the initial kernel launch.