Joey Wang – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2024-10-28T18:18:27Z http://www.open-lab.net/blog/feed/ Joey Wang <![CDATA[Perception Model Training for Autonomous Vehicles with Tensor Parallelism]]> http://www.open-lab.net/blog/?p=81464 2024-05-02T19:01:07Z 2024-04-27T05:00:00Z Due to the adoption of multicamera inputs and deep convolutional backbone networks, the GPU memory footprint for training autonomous driving perception models...]]>

Due to the adoption of multicamera inputs and deep convolutional backbone networks, the GPU memory footprint for training autonomous driving perception models is large. Existing methods for reducing memory usage often result in additional computational overheads or imbalanced workloads. This post describes joint research between NVIDIA and NIO, a developer of smart electric vehicles.

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Joey Wang <![CDATA[Accelerating Embedding with the HugeCTR TensorFlow Embedding Plugin]]> http://www.open-lab.net/blog/?p=37559 2022-08-21T23:52:42Z 2021-09-24T19:00:00Z Recommender systems are the economic engine of the Internet. It is hard to imagine any other type of applications with more direct impact in our daily digital...]]>

Recommender systems are the economic engine of the Internet. It is hard to imagine any other type of applications with more direct impact in our daily digital lives: Trillions of items to be recommended to billions of people. Recommender systems filter products and services among an overwhelming number of options, easing the paradox of choice that most users face. As the amount of data…

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Joey Wang <![CDATA[Introducing NVIDIA Merlin HugeCTR: A Training Framework Dedicated to Recommender Systems]]> http://www.open-lab.net/blog/?p=18990 2024-10-28T18:18:27Z 2020-07-22T00:48:57Z Click-through rate (CTR) estimation is one of the most critical components of modern recommender systems. As the volume of data and its complexity grow rapidly,...]]>

Click-through rate (CTR) estimation is one of the most critical components of modern recommender systems. As the volume of data and its complexity grow rapidly, the use of deep learning (DL) models to improve the quality of estimations has become widespread. They generally have greater expressive power than traditional machine learning (ML) approaches. Frequently evolving data also implies that…

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