NVIDIA’s 2017 Open-Source Deep Learning Frameworks Contributions

Artificial Intelligence, Cloud, CUDA, cuDNN, Development Tools & Libraries, Machine Learning & Artificial Intelligence, TensorRT, Tesla

Nadeem Mohammad, posted Mar 01 2018

Many may not know, NVIDIA is a significant contributor to the open-source deep learning community. How significant? Let’s reflect and explore the highlights and volume of activity from last year.

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Using CUDA Warp-Level Primitives

Accelerated Computing, CUDA, Tesla

Nadeem Mohammad, posted Jan 15 2018

NVIDIA GPUs execute groups of threads known as warps in SIMT (Single Instruction, Multiple Thread) fashion. Many CUDA programs achieve high performance by taking advantage of warp execution.

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Hybridizer: High-Performance C# on GPUs

Accelerated Computing, CUDA

Nadeem Mohammad, posted Dec 15 2017

Hybridizer is a compiler from Altimesh that lets you program GPUs and other accelerators from C# code or .NET Assembly.

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NVIDIA TITAN V Transforms the PC into AI Supercomputer

Artificial Intelligence, Features, CUDA, cuDNN, GeForce, Higher Education/Academia, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Dec 08 2017

NVIDIA introduced TITAN V, the world’s most powerful GPU for the PC, driven by the world’s most advanced GPU architecture, NVIDIA Volta.

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NVIDIA SDK Updated With New Releases of TensorRT, CUDA, and More

Accelerated Computing, Artificial Intelligence, Features, Robotics, Cloud, CUDA, cuDNN, Higher Education/Academia, Machine Learning & Artificial Intelligence, TensorRT, Tesla

Nadeem Mohammad, posted Dec 06 2017

At NIPS 2017, NVIDIA announced new software releases for deep learning and HPC developers.  The latest SDK updates include new capabilities and performance optimizations to TensorRT, CUDA toolkit and the new project CUTLASS library.

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NVIDIA Deep Learning Inference Platform Performance Study

Artificial Intelligence, Cloud, Cluster/Supercomputing, CUDA, Machine Learning & Artificial Intelligence, TensorRT, Tesla

Nadeem Mohammad, posted Dec 04 2017

The NVIDIA deep learning platform spans from the data center to the network’s edge.

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How Jet.com Built a GPU-Powered Fulfillment Engine with F# and CUDA

Accelerated Computing, CUDA, Retail/Etail

Nadeem Mohammad, posted Nov 30 2017

Have you ever looked at your shopping list and tried to optimize your trip based on things like distance to store, price, and number of items you can buy at each store?

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Deep Learning Helps Reconstruct and Improve Optical Microscopy

Artificial Intelligence, CUDA, cuDNN, GeForce, Healthcare & Life Sciences, Higher Education/Academia, Image Recognition, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Nov 22 2017

Researchers from UCLA developed a deep learning approach that could quickly produce more accurate images to aid diagnostic medicine.

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Maximizing Unified Memory Performance in CUDA

Accelerated Computing, CUDA, Tesla

Nadeem Mohammad, posted Nov 20 2017

Many of today’s applications process large volumes of data. While GPU architectures have very fast HBM or GDDR memory, they have limited capacity. Making the most of GPU performance requires the data to be as close to the GPU as possible.

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Generating Photorealistic Images of Fake Celebrities with Artificial Intelligence

Artificial Intelligence, Features, CUDA, cuDNN, Image Recognition, Machine Learning & Artificial Intelligence, Tesla

Nadeem Mohammad, posted Oct 30 2017

Researchers from NVIDIA recently published a paper detailing their new methodology for generative adversarial networks (GANs) that generated photorealistic pictures of fake celebrities.

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