Developer Resources for Energy

Explore open source and NDA samples in a collection of GPU-accelerated algorithms and techniques for the Energy industry, including reverse time migration (RTM), Kirchhoff Migration, SRME, seismic compression, reservoir simulation, Marchenko, and more.

The NVIDIA HPC Software Development Kit (SDK) includes the proven compilers, libraries, and software tools essential to maximizing developer productivity and the performance and portability of high-performance computing (HPC) applications.

NVIDIA® CUDA-X, built on top of NVIDIA CUDA®, is a collection of libraries, tools, and technologies that deliver dramatically higher performance - compared to CPU-only alternatives - across multiple application domains, from artificial intelligence (AI) to high performance computing (HPC).

AI researchers, developers, and data scientists are using NVIDIA AI Enterprise to rapidly deploy, manage, and scale AI workloads in the modern hybrid cloud running on on VMware vSphere with NVIDIA-Certified Systems™.

NVIDIA Omniverse™ is an extensible, open platform built for 3D virtual collaboration and real-time physically accurate simulation. Omniverse combined with NVIDIA Modulus, a framework for developing physics machine learning neural network models, enables digital twins for autonomous vehicles, smart factories, and more.

NVIDIA® Jetson™ brings accelerated AI performance to the edge in a power-efficient and compact form factor. Together with NVIDIA JetPack™ SDK, these Jetson modules open the door for you to develop and deploy innovative products across all industries.

With NGC™, you can quickly deploy AI frameworks with containers, get a head start with pre-trained models or model training scripts, and use domain-specific workflows and Helm charts for the fastest AI implementations, giving you faster time to solution.

NVIDIA Metropolis is an end-to-end application framework built on the NVIDIA EGX platform that simplifies the development, deployment and scale of AI-enabled intelligent video analytics applications, such as retail analytics, traffic management, and automated factory inspections.

The NVIDIA RAPIDS™ suite of open-source software libraries and APIs gives you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs. Licensed under Apache 2.0, RAPIDS is incubated by NVIDIA and based on extensive hardware and data science experience.

Gain an understanding of the various building blocks of NVIDIA Modulus, the basics of physics-informed deep learning, and how the framework integrates with the overall Omniverse platform.

Learn how to reduce complexity and improve portability and efficiency of your code by using a containerized environment for HPC application development.

Learn how to use Jupyter iPython notebooks on a Jetson Nano Developer Kit to build a deep learning classification project with computer vision models. This easy-to-use, powerful computer runs multiple neural networks in parallel.