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NVIDIA enhances its Deep Learning SDK with major updates to three key software components

By Wong Chung Wee - on 20 Jun 2016, 1:59pm

NVIDIA enhances its Deep Learning SDK with major updates to three key software components

(Image source: NVIDIA)

NVIDIA has enhanced its Deep Learning SDK with major updates to three key software components. With these updates, NVIDIA aims to improve GPU acceleration for deep learning data models and applications.

(Image source: NVIDIA)

First of all, NVIDIA has released DIGITS 4, which has added object recognition in its quest to assist data scientists and engineers in solving complex image recognition problems. An immediate application of this new feature is to allow companies to monitor their vehicles for better logistics planning. The object recognition feature can also be applied to advanced video analytics for facial recognition. In terms of its contribution to self-driving cars, it can enhance the car’s system to pick out different objects in traffic; ranging from vehicles, cyclists, and even road signs.

(Image source: NVIDIA)

DIGITS 4 can even assist in medical diagnostics by examining images from X-rays, computed tomography (CT) scans, magnetic resonance imaging (MRI). The new version of DIGITS also adds support for neural network data. And it leverages on NVIDIA GPU Inference Engine (GIE) for more efficient deployments of the trained data models to servers in data centers, automobiles, and even embedded systems! The CUDA-based cuDNN has been given a minor update to version 5.1, to improve its performance on VGG and ResNet style networks. They are deep learning neural networks that have multiple layers of data extractions, which will give them an edge in solving complex problems.

DIGITS 4 is now available for download for registered NVIDIA developers, while cuDNN 5.1 will be made available in early August this year.

(Source: NVIDIA)

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