NVIDIA Developer Blog

Building State-of-the-Art Biomedical and Clinical NLP Models with BioMegatron

Sat, 17 Oct 2020 05:09:20 GMT

With the advent of new deep learning approaches based on transformer architecture, natural language processing (NLP) techniques have undergone a revolution in performance and capabilities. Cutting-edge NLP models are becoming the core of modern search engines, voice assistants, chatbots, and more. Modern NLP models can synthesize human-like text and answer questions posed in natural language. […]html

Preferring Compile-time Errors over Runtime Errors with Vulkan-hpp

Sat, 17 Oct 2020 00:08:45 GMT

One of the most important aspects in professional software development is to detect errors as early as possible. Of course, the best case would be if we couldn’t even write erroneous code. The next best thing is errors that the compiler can detect. The worst cases are runtime errors. The hardest ones are hidden in […]html

Streamlining NVIDIA Driver Deployment on RHEL 8 with Modularity Streams

Fri, 09 Oct 2020 20:49:55 GMT

NVIDIA GPUs have become mainstream for accelerating a variety of workloads from machine learning, high-performance computing (HPC), content creation workflows, and data center applications. For these enterprise use cases, NVIDIA provides a software stack powered by the CUDA platform: drivers, CUDA-X acceleration libraries, CUDA-optimized applications, and frameworks. Deploying the NVIDIA driver is one of the […]html

Adding External Knowledge and Controllability to Language Models with Megatron-CNTRL

Tue, 06 Oct 2020 01:18:32 GMT

Large language models such as Megatron and GPT-3 are transforming AI. We are excited about applications that can take advantage of these models to create better conversational AI. One main problem that generative language models have in conversational AI applications is their lack of controllability and consistency with real-world facts. In this work, we try […]html

Accelerating Intelligent Video Analytics Using Ultra-Efficient 5G Core with Mavenir and NVIDIA ...

Mon, 05 Oct 2020 21:58:47 GMT

For the past decade and a half, an increasing number of businesses have moved their traditional IT applications from on-premises to public clouds. This first phase of the revolution, which you could call “enterprise cloud transformation,” has allowed enterprises to reap the benefits of the scale, expertise, and flexibility of the cloud. The second phase […]html

Accelerating Spark 3.0 and XGBoost End-to-End Training and Hyperparameter Tuning

Mon, 05 Oct 2020 21:26:39 GMT

At GTC Spring 2020, Adobe, Verizon Media, and Uber each discussed how they used Spark 3.0 with GPUs to accelerate and scale ML big data pre-processing, training, and tuning pipelines. Adobe Intelligent Services achieved a 7x performance improvement and 90 percent cost savings with a GPU-based Spark 3.0 and XGBoost intelligent email solution to optimize […]html

Deploying GPUDirect RDMA on the EGX Stack with the NVIDIA Network Operator

Mon, 05 Oct 2020 21:22:07 GMT

Edge computing takes place close to the data source to reduce network stress and improve latency. GPUs are an ideal compute engine for edge computing because they are programmable and deliver phenomenal performance per dollar. However, the complexity associated with managing a fleet of edge devices can erode the GPU’s favorable economics. In 2019, NVIDIA […]html

Announcing NVIDIA NeMo: Fast Development of Speech and Language Models

Mon, 05 Oct 2020 19:23:32 GMT

As a researcher building state-of-the-art speech and language models, you must be able to quickly experiment with novel network architectures. This experimentation may focus on modifying existing network architectures to improve performance, or it may be higher-level experimentation in which speech and language models are combined to build end-to-end applications. A typical starting point for […]html

Making Python Data Science Enterprise-Ready with Dask

Mon, 05 Oct 2020 19:23:29 GMT

At NVIDIA, we are driving change in data science, machine learning, and artificial intelligence. Some of the key trends that drive us are as follows: The rise of Python as the most-used language for data analytics Increased demand for highly usable distributed computing The need for more computational power Open-source software becoming mainstream in industry […]html

Introducing the Ultimate Starter AI Computer, the NVIDIA Jetson Nano 2GB Developer Kit

Mon, 05 Oct 2020 13:26:33 GMT

Today, NVIDIA announced the Jetson Nano 2GB Developer Kit, the ideal hands-on platform for teaching, learning, and developing AI and robotics applications. The NVIDIA Jetson platform introduced six years ago revolutionized embedded computing by delivering the power of artificial intelligence to edge computing devices. NVIDIA Jetson today is widely used in diverse fields such as […]html

Programming the Entire Data Center Infrastructure with the NVIDIA DOCA SDK

Mon, 05 Oct 2020 04:58:22 GMT

Today, in his NVIDIA GTC Fall keynote, CEO Jensen Huang introduced a new kind of processor, the BlueField-2 data processing unit (DPU), a powerful new software development kit for the DPU, DOCA, along with a three year roadmap of DPU and AI innovation. The NVIDIA BlueField-2 DPU is the world’s first data center infrastructure on […]html

Building State-of-the-Art Biomedical and Clinical NLP Models with Bio-Megatron

Mon, 05 Oct 2020 03:25:35 GMT

Securing and Accelerating Cloud Computing Platforms with NVIDIA BlueField-2 DPUs

Mon, 05 Oct 2020 03:24:19 GMT

Cloud technologies are increasingly taking over the worldwide IT infrastructure market. With offerings that include elastic compute, storage, and networking, cloud service providers (CSPs) allow customers to rapidly scale their IT infrastructure up and down without having to build and manage it on their own. The increasing demand for differentiated and cost-effective cloud products and […]html

Accelerating IO in the Modern Data Center: Magnum IO Architecture

Mon, 05 Oct 2020 03:17:00 GMT

Previously the boundary of the unit of computing, sheet metal no longer constrains the resources that can be applied to a single problem or the data set that can be housed. The new unit is the data center. A single box can hold not just one GPU, CPU, and NIC, but a host of cooperating […]html

Announcing the NVIDIA NVTabular Open Beta with Multi-GPU Support and New Data Loaders

Mon, 05 Oct 2020 02:23:53 GMT

Recently, NVIDIA CEO Jensen Huang announced updates to the open beta of NVIDIA Merlin, an end-to-end framework that democratizes the development of large-scale deep learning recommenders. With NVIDIA Merlin, data scientists, machine learning engineers, and researchers can accelerate their entire workflow pipeline from ingesting and training to deploying GPU-accelerated recommenders (Figure 1). While NVIDIA Merlin […]html

Accelerating Recommender Systems Training with NVIDIA Merlin Open Beta

Mon, 05 Oct 2020 01:15:53 GMT

NVIDIA Merlin is an open beta application framework and ecosystem that enables the end-to-end development of recommender systems, from data preprocessing to model training and inference, all accelerated on NVIDIA GPU. We announced Merlin in a previous post and have been continuously making updates to the open beta. In this post, we detail the new […]html

Empowering Smart Hospitals with NVIDIA Clara Guardian from NGC and NVIDIA Fleet Command

Mon, 05 Oct 2020 01:09:04 GMT

Hospitals today are seeking to overhaul their existing digital infrastructure to improve their internal processes, deliver better patient care, and reduce operational expenses. Such a transition is required if hospitals are to cope with the needs of a burgeoning human population, accumulation of medical patient data, and a pandemic. The goal is not only to […]html

Simplifying and Scaling Inference Serving with NVIDIA Triton 2.3

Sun, 04 Oct 2020 00:10:56 GMT

AI, machine learning (ML), and deep learning (DL) are effective tools for solving diverse computing problems such as product recommendations, customer interactions, financial risk assessment, manufacturing defect detection, and more. Using an AI model in production, called inference serving, is the most complex part of incorporating AI in applications. Triton Inference Server takes care of […]html

Training Your Own Voice Font Using Flowtron

Sat, 03 Oct 2020 23:40:11 GMT

Recent conversational AI research has demonstrated automatically generating high quality, human-like audio from text. For example, you can use Tacotron 2 and WaveGlow to convert text into high quality, natural-sounding speech in real time. You can also use FastPitch to generate mel spectrograms in parallel, achieving good speedup compared to Tacotron 2. However, current text-to-speech […]html

Analyzing Genome Sequence Data on AWS with WekaFS and NVIDIA Clara Parabricks Pipelines

Fri, 02 Oct 2020 17:11:53 GMT

Whole genome sequencing has become an important and foundational part of genomic research, enabling researchers to identify genetic signatures associated with diseases, differentiate sequencing errors from biological signals, and better characterize the genomes of various organisms. With the ongoing COVID-19 pandemic threatening the globe, characterizing, and understanding genomes is now more crucial than ever. Commercially […]html