NVIDIA Frameworks

NVIDIA Frameworks
from AMBER AI & Data Science Solutions

Deep Learning Frameworks

Deep learning frameworks are essential for designing, training, and validating deep neural networks. These frameworks provide building blocks that allow users to interact with deep learning models through a high-level programming interface. Some of the most widely-used deep learning frameworks include TensorFlow, PyTorch, DGL, and PyTorch Geometric, among others. To achieve high-performance and multi-GPU-accelerated training, these frameworks rely on GPU-accelerated libraries such as cuDNN, NCCL, and DALI. These libraries enable faster and more efficient processing of deep learning models, allowing for larger-scale and more complex neural networks to be trained and evaluated.

Riva Speech AI SDK

NVIDIA Riva

NVIDIA® Riva is an AI software development kit (SDK) that accelerates speech recognition using GPUs. It is designed to enable the creation and deployment of AI pipelines that are highly customizable, deliver real-time results, and achieve outstanding accuracy across a range of environments, including cloud, on-premises, edge, and embedded devices.

How to get started with NVIDIA Riva

Purchase Riva Enterprise for Deployment at Scale
If you're interested in using NVIDIA Riva for large-scale deployments, consider purchasing Riva Enterprise. This option provides unlimited usage on all clouds, access to NVIDIA AI experts, and long-term support to help you get started with Riva.
Get into Riva AI Workflows
Accelerate your AI development process with pre-packaged workflows for audio transcription and intelligent virtual assistants available through the NVIDIA Riva Enterprise software, providing you with access to Riva AI workflows.
Download Containers and Models for Development
As a member of the NVIDIA Developer Program, you can access free Riva containers and pretrained models for developing voice-enabled applications across cloud, data center, and embedded platforms. These resources can help accelerate your development process. You can download them from NVIDIA NGC™ .

RAPIDS: High-Performance Data Science

With RAPIDS, you can achieve high-performance in data science tasks by leveraging the power of GPUs. This will allow you to accelerate your workflows in machine learning and AI with ease.

By using high-speed GPU computing, RAPIDS can run your entire data science workflows much faster, allowing you to parallelize data loading, data manipulation, and machine learning processes. This results in up to 50 times faster end-to-end data science pipelines.

Why RAPIDS?

The field of data science and machine learning is critical to the world's computing industry, and even small improvements in analytics models can lead to significant financial gains. Data scientists put in a lot of work to create highly accurate and performant models by constantly training, evaluating, iterating, and retraining their models. RAPIDS™ helps accelerate this process from days to minutes, allowing for faster development and deployment of models that create value. NVIDIA LaunchPad offers hands-on experience with RAPIDS labs, and NVIDIA AI Enterprise provides comprehensive support for your AI projects at every stage.

Establishing a High-Performance Ecosystem

RAPIDS is a collection of open-source software libraries and APIs that can execute data science workflows entirely on GPUs, resulting in a significant reduction of training times from days to minutes. Based on the NVIDIA® CUDA-X AI™ platform, RAPIDS brings together years of advancement in areas such as graphics, machine learning, deep learning, and high-performance computing (HPC).

Faster Processing Time
In the field of data science, increased computational power translates to quicker insights. RAPIDS employs NVIDIA CUDA® technology to speed up workflows by running the complete data science training process on GPUs. This can minimize model training times from days to minutes.
Utilize Consistent Tools
With RAPIDS, working with GPUs and the communication protocols of the data center infrastructure are simplified and abstracted away. This allows for an easier and more streamlined approach to data science. As Python and other high-level languages become more popular among data scientists, providing accelerated performance without requiring code changes is crucial for reducing development time.
Scalable Deployment Options
RAPIDS can be run anywhere—cloud or on-prem. You can easily scale from a workstation to multi-GPU servers to multi-node clusters, as well as deploy it in production with Dask, Spark, MLFlow, and Kubernetes.
Thanks to its flexible architecture, RAPIDS can be deployed in a variety of environments, from the cloud to on-premises infrastructure. With support for scaling from a single workstation to multi-GPU servers and multi-node clusters, RAPIDS can handle your data science needs at any scale. Plus, it can be seamlessly integrated with popular tools like Dask, Spark, MLFlow, and Kubernetes to support your production deployments.
Enterprise-Ready Data Science
Access to dependable support is crucial for organizations that rely on data science to gain mission-critical insights. NVIDIA AI Enterprise is an all-in-one AI software suite that provides access to Global NVIDIA Enterprise Support, which includes guaranteed response times, priority security notifications, regular updates, and the expertise of NVIDIA AI professionals.

NVIDIA Clara: Support of Healthcare AI Development, Research and Innovation

NVIDIA Clara is a platform that offers a centralized location for developers and data scientists in the Healthcare & Life Sciences industry to access technical resources, news, and software development kits (SDKs) to support their work in healthcare AI development, research, and innovation.

What is NVIDIA Clara?

NVIDIA Clara is a comprehensive platform of AI tools and frameworks designed for healthcare professionals, medical device manufacturers, and researchers who aim to improve healthcare delivery and speed up the drug discovery process using AI-based solutions. Clara offers a range of specialized tools, pre-trained AI models, and accelerated applications that enable breakthroughs in various healthcare domains such as genomics, imaging, natural language processing, medical devices, drug discovery, and smart hospitals.

Develop with NVIDIA Clara

Healthcare Imaging and Devices
NVIDIA Clara™ Holoscan is an AI-powered computing platform designed for medical devices. It integrates hardware systems with low-latency sensor and network connectivity, optimized libraries for data processing and AI, and core microservices to run streaming, imaging, and other applications. The platform supports a range of deployment options, from embedded to edge to cloud.
Healthcare IOT
Leverage application frameworks offered by NVIDIA Clara to develop smart hospital applications, which can enhance patient care, optimize operational efficiency, and speed up medical imaging workflows.
Biopharma
Get access to a variety of frameworks, applications, and AI models in fields such as genomics, proteomics, microscopy, virtual screening, computational chemistry, visualization, clinical imaging, and natural language processing to support your biopharmaceutical research and development efforts.
Genomics
Leverage accelerated applications for somatic, germline, and structural variant workflows to simplify tasks such as whole genome, exome, RNA, and cancer sequencing.