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Nvidia developer blog

This year proved to be a banner year for the NVIDIA Developer Blog, publishing over 80 new technical articles.

Given this year’s pace, it’s easy to miss out on cool new insights and information, so let’s take a little time to review the year.

NVIDIA launched the shiny new Turing architecture this year, which prompted a number of Turing-related articles, particularly about ray tracing.

I want to highlight three timeless tutorials which provide ongoing resources for new and experienced programmers using NVIDIA technologies.

Evaluating the Benefits of Many-Core Programming Models Using Scientific Kernels: A Case Study

Case studies constitute a modern interdisciplinary and valuable teaching practice which plays a critical and fundamental role in the development of new skills and the formation of new knowledge.

This research studies the behavior and performance of two interdisciplinary and widely adopted scientific kernels, a Fast Fourier Transform and Matrix Multiplication.

Both routines are implemented in the two current most popular many-core programming models CUDA and OpenACC.

A Fast Fourier Transform (FFT) samples a signal over a period of time and divides it into its frequency components, computing the Discrete Fourier Transform (DFT) of a sequence.

This research also shows that the nature of the problem plays a crucial role in determining what many-core model will provide the highest benefit in performance.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

An Introduction to GPU Programming with CUDA

If you can parallelize your code by harnessing the power of the GPU, I bow to you. GPU code is usually abstracted away by by the popular deep learning ...

NVIDIA Deep Learning Course: Class #1 – Introduction to Deep Learning

Register for the full course at Also, watch more classes on deep learning: This first in a .

NVIDIA's Image Restoration AI: Almost Perfect

The paper "Noise2Noise: Learning Image Restoration without Clean Data" and its source code are available here: 1. 2

Best Laptop for Machine Learning

What kind of laptop should you get if you want to do machine learning? There are a lot of options out there and in this video i'll describe the components of an ...

Ansible: Clean Ubuntu 18.04 to CUDA 10, PyTorch 1.0, fastai deep learning machine

20x speed video showing configuration of GCE Ubuntu 18.04 instance with 8 vCPUs, 30 GB memory and a NVIDIA Tesla V100 with miniconda3, PyTorch 1.0 ...

DGX Station vs. DIY

As a developer, researcher, or data scientist, you want to bring the power of AI to your work. You could go to IT to get a server, but you want the control and ...

NVIDIA Developer How To Series: Introduction to Recurrent Neural Networks in TensorRT

NVIDIA TensorRT is a high-performance deep learning inference optimizer and runtime that delivers low latency and high-throughput. TensorRT can import ...

NVIDIA Deep Learning Course: Class #5 - Getting started with Torch7

Register for the full course and find the Q&A log at Torch is a scientific computing framework. It uses an easy ..

TecHeal Xtreme Build for Artificial Intelligence & Deep Learning

Hello Everyone, We are back with our Extreme PC Build for Artificial Intelligence & Deep Learning. This build is purely design for Programmers and Artificial ...

Distributed TensorFlow (TensorFlow Dev Summit 2017)

TensorFlow gives you the flexibility to scale up to hundreds of GPUs, train models with a huge number of parameters, and customize every last detail of the ...