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[skip ci] Add list of CCCL users to README #474

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Sep 22, 2023
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[skip ci] Add list of CCCL users to README #474

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[skip ci] Add list of CCCL users.
jrhemstad Sep 22, 2023
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[skip ci] Add link to automatically bring up README in editor.
jrhemstad Sep 22, 2023
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Update README.md
jrhemstad Sep 22, 2023
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28 changes: 28 additions & 0 deletions README.md
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Expand Up @@ -363,3 +363,31 @@ The deprecation period will depend on the impact of the change, but will usually
## CI Pipeline Overview

For a detailed overview of the CI pipeline, see [ci-overview.md](ci-overview.md).

## Projects Using CCCL

Does your project use CCCL? [Open a PR to add your project to this list!](https://github.com/NVIDIA/cccl/edit/main/README.md)

- [AmgX](https://github.com/NVIDIA/AMGX) - Multi-grid linear solver library
- [ColossalAI](https://github.com/hpcaitech/ColossalAI) - Tools for writing distributed deep learning models
- [cuDF](https://github.com/rapidsai/cudf) - Algorithms and file readers for ETL data analytics
- [cuGraph](https://github.com/rapidsai/cugraph) - Algorithms for graph analytics
- [cuML](https://github.com/rapidsai/cuml) - Machine learning algorithms and primitives
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- [cuSOLVER](https://developer.nvidia.com/cusolver) - Dense and sparse linear solvers
- [cuSpatial](https://github.com/rapidsai/cuspatial) - Algorithms for geospatial operations
- [GooFit](https://github.com/GooFit/GooFit) - Library for maximum-likelihood fits
- [HeavyDB](https://github.com/heavyai/heavydb) - SQL database engine
- [HOOMD](https://github.com/glotzerlab/hoomd-blue) - Monte Carlo and molecular dynamics simulations
- [HugeCTR](https://github.com/NVIDIA-Merlin/HugeCTR) - GPU-accelerated recommender framework
- [Hydra](https://github.com/MultithreadCorner/Hydra) - High-energy Physics Data Analysis
- [Hypre](https://github.com/hypre-space/hypre) - Multigrid linear solvers
- [LightSeq](https://github.com/bytedance/lightseq) - Training and inference for sequence processing and generation
- [PyTorch](https://github.com/pytorch/pytorch) - Tensor and neural network computations
- [Qiskit](https://github.com/Qiskit/qiskit-aer) - High performance simulator for quantum circuits
- [QUDA](https://github.com/lattice/quda) - Lattice quantum chromodynamics (QCD) computations
- [RAFT](https://github.com/rapidsai/raft) - Algorithms and primitives for machine learning
- [TensorFlow](https://github.com/tensorflow/tensorflow) - End-to-end platform for machine learning
- [TensorRT](https://github.com/NVIDIA/TensorRT) - Deep leaning inference
- [tsne-cuda](https://github.com/CannyLab/tsne-cuda) - Stochastic Neighborhood Embedding library
- [Visualization Toolkit (VTK)](https://gitlab.kitware.com/vtk/vtk) - Rendering and visualization library
- [XGBoost](https://github.com/dmlc/xgboost) - Gradient boosting machine learning algorithms