integrate easily into existing TensorFlow or PyTorch training pipelines by using a similar API.prepare batches asynchronously into the GPU to avoid CPU-GPU communication.process datasets that don’t fit within the GPU or CPU memory by streaming from the disk.remove bottlenecks from dataloading by processing large chunks of data at a time instead of item by item.The NVTabular dataloaders can lead to a speedup that is nine times faster than the same training pipeline used with the GPU. Therefore, we’ve developed custom, highly-optimized dataloaders to accelerate existing TensorFlow and PyTorch training pipelines. When training deep learning recommender system models, dataloading can be a bottleneck. NVTabular provides seamless integration with common deep learning frameworks, such as TensorFlow, PyTorch, and HugeCTR.
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focus on what to do with the data and not how to do it by using abstraction at the operation level.process datasets that exceed GPU and CPU memory without having to worry about scale.prepare datasets quickly and easily for experimentation so that more models can be trained.NVTabular is also capable of transformation speedups that can be 100 times to 1,000 times faster than transformations taking place on optimized CPU clusters. NVTabular offers a high-level API that can be used to define complex data transformation workflows. It is designed to quickly and easily manipulate terabyte-size datasets that are used to train deep learning based recommender systems. NVTabular is essentially the ETL component of the Merlin ecosystem. NVTabular is a feature engineering and preprocessing library for tabular data. NVIDIA Merlin consists of the following open source libraries: deploy data transformations and trained models to production with only a few lines of code.scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory.accelerate existing training pipelines in TensorFlow, PyTorch, or FastAI by leveraging optimized, custom-built dataloaders.transform data (ETL) for preprocessing and engineering features.NVIDIA Merlin is a scalable and GPU-accelerated solution, making it easy to build recommender systems from end to end. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, which is all accessible through easy-to-use APIs. Merlin includes tools to address common ETL, training, and inference challenges. It enables data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs.