Simulation and Modeling

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.

r large-scale simulations


Researchers are using GPUs to run their large-scale simulations faster, gain deeper insights sooner, and publish their findings quicker.

GPU-powered Systems


Engineers in mechanical engineering, geosciences, and manufacturing are modeling complex designs on GPU-powered systems to analyze their work.



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 is a molecular dynamics application designed to simulate Newtonian equations of motion for systems with hundreds to millions of particles.


Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a software application designed for molecular dynamics simulations.


Nanoscale Molecular Dynamics (NAMD) is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems.

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.


Accelerated Simulation and Modeling in Action

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. 

Weather forecasting and climate modeling

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.

Simulate COVID-19

Simulate COVID-19

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.

Accelerate Financial Models

Accelerate Financial Models

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.

CPU Based Solutions

Speed Up Engineering 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.

Learn more about simulation through session and demo videos, or get started with the NVIDIA Developer Blog.