JetsonHacks

Developing on NVIDIA® Jetson™ for AI on the Edge

Articles

Deep Learning
Microsoft Research just published a paper on using FPGAs to accelerate machine learning: Accelerating Deep Convolutional Neural Networks Using Specialized Hardware. This is an interesting alternative to using GPUs for […]
Update On April 2nd, Microsoft announced that they are consolidating the Kinect for Windows around a single sensor. They will discontinue “Kinect for Windows V2” described below. However the replacement […]
A great article over at the NVIDIA Parallel FORALL blog: BIDMach: Machine Learning at the Limit with GPUs by John Canny over at Berkeley. Introduction: Deep learning has made enormous […]
Ian King over at Dark Sol Workshop designed and built an enclosure for the Jetson: Go over and check it out on their blog: Dark Sol Workshop: Jetson TK1 Dev […]
The Jetson TK1 has a SD Card reader. Most Secure Digital (SD) cards come from the factory formatted as ExFat which is the most common format for Windows machines and […]
Several years ago, the Sony PlayStation 3 Eye webcam was the staple of DIY Computer Vision projects. I happened to have several of them lying about from past projects. Here’s […]
NVIDIA’s cuDNN is a GPU-accelelerated library of primitives for deep neural networks, which is designed to be integrated into higher-level machine learning frameworks, such as UC Berkeley’s Caffe deep learning […]
Back in October 2014, Google’s Pete Warden wrote an interesting article: How to run the Caffe deep learning vision library on Nvidia’s Jetson mobile GPU board. At the time, I […]
Facebook AI Research (FAIR) has open sourced Deep Learning CUDA extensions. The extensions are for Torch, a scientific computing framework with wide support for machine learning algorithms. In the Facebook […]
Computación y Sistemas has published an interesting paper: Simulating and Visualizing Real-Time Crowds on GPU Clusters. Here’s the source of the paper: Computación y Sistemas. Several different NVIDIA GPUs were […]

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