Energy Industry Developer Resources

A hub of SDKs, technical resources, and more for developers working in the energy industry.

App Frameworks and SDKs


NVIDIA CUDA-X

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).


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RAPIDS

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.


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NVIDIA EGX

The NVIDIA EGX™ platform delivers the power of accelerated AI computing to the edge with an easy-to-deploy, cloud-native software stack, a range of validated servers and devices, Helm charts to ease deployment of AI applications, and a vast ecosystem of partners who offer EGX through their products and services.


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PGI OpenACC

The PGI Community Edition with OpenACC® offers scientists and researchers a quick path to accelerated computing with less programming effort. By inserting compiler “hints” or directives into your C, C++, or Fortran code, the PGI OpenACC compiler will offload and run your code on the GPU and CPU.


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HPC SDK

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.


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NGC

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.


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Upcoming GTC Sessions for Energy

Machine Learning with OpenShift and NVIDIA GPUs at ExxonMobil

Learn how to use NVIDIA GPUs on an OpenShift platform and how data scientists and engineers at ExxonMobil are using open-source containers for AI and machine learning.

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SaltNet: A Production-Scale Automated Salt Model Building Pipeline

Learn about the development of a production-scale workflow that leverages NVIDIA GPUs to accurately and quickly identify salt structure.

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Reservoir Simulation Evolved: From Kepler to Ampere and Beyond

Learn the benefits and capabilities of full GPU acceleration for reservoir modeling, including a historical perspective on performance and forward forecast.

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See all the sessions for energy here.

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Browse by Resource Type

Accelerating Machine Learning at the Edge: Real-Time Well Engineering

Real-time machine learning enables quantitative analytics at the edge. To calculate the results in a satisfactory time window, both the hardware and software should be up to the task.


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Fully Exploiting a GPU Supercomputer for Seismic Imaging

This demonstration shows the porting of modern seismic applications like reverse time migration, full waveform inversion, and one-way migration to the GPU-accelerated Pangea III supercomputer.


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Autonomous Anomaly Detection for Dense-Sensor IoT Prognostics

Low latencies and high throughputs are critical to achieving real-time streaming prognostics, particularly in cloud environments. Learn how NVIDIA GPU acceleration of MSET2, Oracle’s advanced machine learning pattern-recognition method, yields substantial latency reduction and throughput gains.


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Netherlands-Based Rolloos Taps AI to Make Oil Rigs Safer for Workers

Company offers a network of cameras, sensors, and deep learning to locate workers in unsafe spots and alert them before an accident occurs.


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How AI is Providing Digital Twins for Predictive Maintenance in Oil and Gas

The oil and gas industry faces serious challenges, including the costs of maintaining its aging infrastructure. Deep learning, GPUs, and the concept of “Digital Twins” offer enormous potential for predictive maintenance.


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How GPUs are Transforming the Oil and Gas Industry

Oil and gas companies are in the data business as much as they are in the hydrocarbon business. To stay ahead of the competition, they need to derive insights from the massive amounts of sensor, geolocation, weather, drilling, and seismic data they generate.


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Leveraging Accelerated Computing to Transform the Energy Industry

Stone Ridge Technology and NVIDIA discuss how to mitigate risks, increase efficiency, and reduce uncertainty in integrated production and reservoir systems for oil and gas.


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Remote Work with NVIDIA: Oil and Gas Exploration from Home

GeoComputing Group, Kosmos Energy, and NVIDIA discuss solutions that allow users to stream their most robust applications and datasets without compromising security.


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NVIDIA DEEP LEARNING INSTITUTE

The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI and accelerated computing to solve real-world problems. Training is available as self-paced, online courses or in-person, instructor-led workshops.


High Performance Computing with Containers

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


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Fundamentals of Accelerated Data Science with RAPIDS

Learn how to perform multiple analyses on large datasets using RAPIDS, a collection of libraries that allows end-to-end GPU acceleration for data science.


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AI Workflows for Intelligent Video Analytics with DeepStream

Learn how to build hardware-accelerated applications for intelligent video analytics (IVA) with DeepStream and deploy them at scale to transform video streams into insights.


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Fundamentals of Accelerated Computing with CUDA C/C++

Learn how to accelerate and optimize existing C/C++ CPU-only applications to leverage the power of GPUs using the most essential CUDA techniques and the NVIDIA Nsight™ Systems profiler.


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Fundamentals of Accelerated Computing with OpenACC

Explore how to build and optimize heterogeneous applications on multiple GPU clusters using OpenACC, a high-level GPU programming language.


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