NVIDIA Deep Learning Institute Releases Accelerated Data Science Teaching Kit

The NVIDIA Deep Learning Institute (DLI) recently released the Accelerated Data Science Teaching Kit, co-developed with Professor Polo Chau of the Georgia Institute of Technology and Professor Xishuang Dong of Prairie View A&M University. The comprehensive teaching materials cover basic and advanced topics in data acquisition and preprocessing, accelerated data science with RAPIDS, scalable and […]

What is accelerated computing?  |  NVIDIA blog

Accelerated computing is buzzing in the background and makes life better at home even on a quiet night. It prevents credit card fraud when you buy a movie to stream. They’ll recommend a dinner you like and ensure quick delivery. Perhaps it even helped the director of the film win an Oscar for breathtaking images. […]

High-level block diagram of SE(3)-Transformer architecture.

SE (3) transformers are versatile neural graph networks that were presented at NeurIPS 2020. NVIDIA has just released an open source optimized implementation that uses 9x less memory and is up to 21x faster than the official base implementation. SE (3) transformers are useful for solving problems with geometric symmetries, such as: B. small molecule […]

GPU accelerated tools added to NVIDIA Clara Parabricks v3.6 for cancer and germline analysis

The release of NVIDIA Clara Parabricks v3.6 expands its suite of powerful genome analysis tools with new applications for variant calling, annotation, filtering and quality control. NVIDIA Clara Parabricks now offers over 33 accelerated tools for every phase of genome analysis and offers GPU-accelerated bioinformatics pipelines that can be scaled for any workload. As genomes […]

Build NVIDIA GPU accelerated pipelines on Azure Synapse Analytics with RAPIDS

Azure recently announced support for NVIDIA’s T4 Tensor Core Graphics Processing Units (GPUs), which are optimized for low-cost deployment of machine learning inference or analytics workloads. With Apache Spark ™ deployments tailored to NVIDIA GPUs and preinstalled libraries, Azure Synapse Analytics provides an easy way to leverage GPUs for a variety of compute and machine […]

A collection of images.

Based on the capabilities of GPUs, a team at Facebook AI Research developed a faster and more efficient way for AI to perform similarity searches. That to learn, Published in IEEE transactions on big data, creates a deep learning algorithm that is able to process and compare high-dimensional data from media that is significantly faster […]

Talking Intel Accelerated News and Process Tech with TechTechPotato

In this episode of Two And A Half Geeks, Dr. Ian Cutress of TechTechPotato and Anandtech joined us for a lively discussion about the revelations made during the ‘Intel Accelerated’ event and what it all means, from chip-level transistor technology to process node naming and everything in between … Show notes: 02:22 – Introducing Ian […]

Accelerated model inference for machine learning in Google Cloud Dataflow with NVIDIA GPUs

In partnership with NVIDIA, Google Cloud announced today that Dataflow is introducing GPUs to the world of big data processing to open up new possibilities. With Dataflow GPU, users can now leverage the power of NVIDIA GPUs in their machine learning inference workflows. Here we show you how you can access these performance benefits with […]

Accelerated production AI with pre-trained models and Transfer Learning Toolkit 3.0

NVIDIA today announced new pre-trained models and the general availability of the Transfer Learning Toolkit (TLT) 3.0, a core component of NVIDIA’s platform-driven Train, Adapt, and Optimize (TAO) workflow for building AI. The new version includes a variety of high-precision and powerful pre-trained models for computer vision and conversational AI, as well as a range […]

Beginner’s Guide to GPU- Accelerated Event Stream Processing in Python

This tutorial is the seventh installment of introductions to the RAPIDS ecosystem. The series explores and discusses various aspects of RAPIDS that allow its users solve ETL (Extract, Transform, Load) problems, build ML (Machine Learning) and DL (Deep Learning) models, explore expansive graphs, process geospatial, signal, and system log data, or use SQL language via […]