message: Updates for the 2/22 release
diff: # <img src="docs/user_guide_src/merlin_logo.png" alt="logo" width="85"/> Merlin: HugeCTR #
  -HugeCTR is a GPU-accelerated recommender framework designed to distribute training across multiple GPUs and nodes and estimate Click-Through Rates (CTRs). HugeCTR supports model-parallel embedding tables and data-parallel neural networks and their variants such as [Wide and Deep Learning (WDL)](https://arxiv.org/abs/1606.07792), [Deep Cross Network (DCN)](https://arxiv.org/abs/1708.05123), [DeepFM](https://arxiv.org/abs/1703.04247), and [Deep Learning Recommendation Model (DLRM)](https://arxiv.org/abs/1906.00091). HugeCTR is a component of [NVIDIA Merlin Open Beta](https://developer.nvidia.com/nvidia-merlin), used to build large-scale deep learning recommender systems. For additional information, see [HugeCTR User Guide](docs/hugectr_user_guide.md).
  +HugeCTR is a GPU-accelerated recommender framework designed to distribute training across multiple GPUs and nodes and estimate Click-Through Rates (CTRs). HugeCTR supports model-parallel embedding tables and data-parallel neural networks and their variants such as [Wide and Deep Learning (WDL)](https://arxiv.org/abs/1606.07792), [Deep Cross Network (DCN)](https://arxiv.org/abs/1708.05123), [DeepFM](https://arxiv.org/abs/1703.04247), and [Deep Learning Recommendation Model (DLRM)](https://arxiv.org/abs/1906.00091). HugeCTR is a component of [NVIDIA Merlin Open Beta](https://developer.nvidia.com/nvidia-merlin), which is used to build large-scale deep learning recommender systems. For additional information, see [HugeCTR User Guide](docs/hugectr_user_guide.md).
  Design Goals:
  * **Fast**: HugeCTR is a speed-of-light CTR model framework that can [outperform](performance.md) popular recommender systems such as TensorFlow (TF).
  