Power Breakthroughs With GPU-Accelerated Simulations
GPUs speed up high-performance computing (HPC) workloads by parallelizing parts of the code that are compute intensive. This enables researchers, scientists, and engineers across scientific domains to run their simulations in a fraction of the time and make discoveries faster.
Who Uses Simulation and Modeling?
Simulation and modeling are used in a variety of industries. They can be used by researchers to create new drugs to fight diseases, engineers to simulate intricate real-world problems, and analysts to create financial models.
Researchers
Researchers are using GPUs to run their large-scale simulations faster, gain deeper insights sooner, and publish their findings quicker.
Engineers
Engineers in mechanical engineering, geosciences, and manufacturing are modeling complex designs on GPU-powered systems to analyze their work.
Analysts
Financial organizations are making real-time decisions by extracting insights from massive datasets using NVIDIA GPUs.
Accelerate Your Simulation Workloads
From fluid simulations to molecular dynamics, applications help scientists, engineers, and researchers do their work across various fields. Today, thousands of these applications are GPU-accelerated, allowing researchers to do their life’s work more efficiently. Key HPC applications are available from the NVIDIA NGC™ catalog.
GROMACS
GROMACS is a molecular dynamics application designed to simulate Newtonian equations of motion for systems with hundreds to millions of particles.
To explore the performance improvements of some key HPC applications, visit the NVIDIA Developer Zone.To get started with these GPU-accelerated applications, visit NVIDIA NGC.
Develop GPU-Accelerated Applications with NVIDIA HPC SDK
A Comprehensive Suite of Compilers, Libraries, and Tools for HPC
The NVIDIA HPC SDK includes the proven compilers, libraries, and software tools essential to maximizing developer productivity and the performance and portability of HPC modeling and simulation applications.
Widely used HPC applications, including VASP, Gaussian, ANSYS Fluent, GROMACS, and NAMD, use CUDA®, OpenACC®, and GPU-accelerated math libraries to deliver breakthrough performance. You can use these same software tools to accelerate your applications with NVIDIA GPUs and achieve dramatic speedups and power efficiency.
Develop AI-Powered Weather Analysis With Omniverse Blueprint for Earth-2 Weather Analytics
The NVIDIA Omniverse™ Blueprint for Earth-2 Weather Analytics is a reference architecture, meant for independent software vendors and their application developers to build AI-augmented simulation and visualization pipelines for the climate and weather domain. This reference can significantly accelerate the development of climate tech applications for weather and climate analysis, planning, and risk mitigation and for developing digital twins of weather and climate.
Leading computer-aided engineering (CAE) software vendors—including Ansys, Altair, Cadence, Siemens, and Synopsys—are accelerating their design tools to run faster with the NVIDIA Blackwell platform.
With such accelerated software, along with NVIDIA CUDA-X™ libraries and blueprints to further optimize performance, industries such as automotive, aerospace, energy, manufacturing, and life sciences can significantly reduce product development.
Simulation and modeling have diverse use cases, which can be used in a variety of different industries such as healthcare, finance, manufacturing, and earth sciences.
Predict Weather Patterns
Explore how simulation is used in weather forecasting and climate modeling—including how automated feature detection can identify threats from severe weather, solar storms, and near-earth objects and how accelerating models and data assimilation techniques can produce more accurate predictions.
Learn how simulation in research can help address many problems, including the COVID-19 pandemic. Combining the compute power of 200,000+ NVIDIA GPUs and additional computing resources contributed by volunteers, the Folding@Home project has performed an exascale simulation of the spike protein.
Take a dive into what HPC modeling can achieve outside of scientific research. It’s also used in the financial sector to do modeling and analysis. As financial models grow in size and sophistication, data scientists and developers are increasingly turning to HPC to accelerate their algorithms and simulations.
Learn how simulation and modeling enables reservoir engineers to develop more accurate, robust, and predictive models faster, using fewer hardware resources than CPU-based solutions.