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This project implements the well known multi GPU Jacobi solver with different multi GPU Programming Models: single_threaded_copy Single Threaded using cudaMemcpy for inter GPU communication multi_threaded_copy Multi Threaded with OpenMP using cudaMemcpy for inter GPU communication multi_threaded_copy_overlap Multi Threaded with OpenMP using cudaMemcpy for inter GPU communication with overlapping c
LATEST RELEASE / DEVELOPMENT VERSION: The main branch tracks the latest released beta version: 0.11.0. For the latest development version, checkout the develop branch. DISCLAIMER: The beta release is undergoing active development and may be subject to changes and improvements, which could cause instability and unexpected behavior. We currently do not recommend deploying this beta version in a prod
github.com/NVIDIA-Merlin
NVTabular is a feature engineering and preprocessing library for tabular data that is designed to easily manipulate terabyte scale datasets and train deep learning (DL) based recommender systems. It provides high-level abstraction to simplify code and accelerates computation on the GPU using the RAPIDS Dask-cuDF library. NVTabular is a component of NVIDIA Merlin, an open source framework for build
github.com/NVIDIAGameWorks
Warp is a Python framework for writing high-performance simulation and graphics code. Warp takes regular Python functions and JIT compiles them to efficient kernel code that can run on the CPU or GPU. Warp is designed for spatial computing and comes with a rich set of primitives that make it easy to write programs for physics simulation, perception, robotics, and geometry processing. In addition,
Pretrain and finetune 🤗Hugging Face models via AutoModel Nemo Framework's latest feature AutoModel enables broad support for 🤗Hugging Face models, with 25.02 focusing on AutoModelForCausalLM in the text generation category. Future releases will enable support for more model families such as Vision Language Model. Training on Blackwell using Nemo NeMo Framework has added Blackwell support, with 2
github.com/NVIDIA-AI-IOT
The NVIDIA Data Loading Library (DALI) is a GPU-accelerated library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built in data loaders and data iterators in popular deep learning frameworks. Deep l
nv-wavenet is a CUDA reference implementation of autoregressive WaveNet inference. In particular, it implements the WaveNet variant described by Deep Voice. nv-wavenet only implements the autoregressive portion of the network; conditioning vectors must be provided externally. More details about the implementation and performance can be found on the NVIDIA Developer Blog. Channel counts are provide
CUTLASS 3.8.0 - January 2025 CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-matrix multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN. CUTLASS decomposes these "moving parts" into reusab
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