San Francisco, CA – Rescale and Dassault Systèmes are announcing a technology partnership to provide users of SIMULIA Abaqus Finite Element Analysis (FEA) the ability to run their simulations in the cloud using Rescale’s end-to-end, web-based platform.

“Dassault Systèmes’ SIMULIA application is a recognized leader in simulation technologies, and we are thrilled to expand our relationship with them. As a SIMULIA technology partner, we look forward to helping Abaqus users unleash the full potential of their powerful software by running engineering analyses on Rescale’s platform,” said Rescale CEO Joris Poort.

Rescale provides a comprehensive suite of features – on-demand access to high-performance computing, full integration with simulation tools such as Abaqus, and an intuitive user interface, all delivered through any web browser. In addition, Rescale also adheres to the highest industry standards for security at every level of the Rescale experience; engineers can transfer, manage and store data with the utmost confidence. Interested customers can approach Rescale directly for more information on running projects.

Dennis Corain, manager of SIMULIA strategic partnerships for Dassault Systèmes, explained, “We have had several customers approach us about how to get the most out of the cloud for their Abaqus simulations. Rescale delivers a comprehensive, easy-to-use service in this space, especially for our most demanding customers. We are very excited to work closely with them moving forward. This is a big win for our customers.”

For more information about Rescale, Dassault Systèmes, and SIMULIA:

Dassault Systèmes:

About Rescale:

Rescale provides a secure, pay-per-use, web-based platform that helps engineers and scientists build, compute, and analyze large simulations on demand. Incorporated in 2011, Rescale is located in San Francisco, CA and works with customers in the aerospace, automotive, oil & gas, and life sciences industries.

About Dassault Systèmes:

Dassault Systèmes, the 3DEXPERIENCE Company, provides businesses and people with virtual universes to imagine sustainable innovations. Its world-leading solutions transform the way products are designed, produced, and supported. Dassault Systèmes’ collaborative solutions foster social innovation, expanding possibilities for the virtual world to improve the real world. The group brings value to over 150,000 customers of all sizes, in all industries, in more than 140 countries. For more information, visit SIMULIA is a registered trademark of Dassault Systèmes.

This article was written by Rescale.


Visualization of a molecular dynamics simulation using DPPC membrane with an embedded protein(image courtesy of Justin Lemkul).

Gromacs was developed by ScalaLife and funded by the European Research Council. Gromacs is an open-source, versatile package designed for analyzing molecular dynamics in biochemical molecules. Due to its popularity, we decided to use Gromacs to demonstrate the steps required to parallelize a single job across multiple dynos (i.e., computing cores). You can find the original basic Gromacs tutorial here, and another parallelization tutorial here.

Our example simulates a phospholipid membrane, consisting of 1024 dipalmitoylphosphatidylcholine (DPPC) lipids in a bilayer configuration with 23 water molecules per lipid, for a total of 121,846 atoms. When you encounter large-scale problems, consider parallelizing your job across multiple dynos to reduce runtime. If you can successfully parallelize your job across two dynos, you could potentially reduce your job’s runtime by 50%.

When we parallelized our example across four dynos, the runtime was cut in half.


As you can see, we didn’t experience a 4x improvement in runtime when parallelizing across four cores (when compared to running on one core). There are delays associated with (a) job decomposition and (b) passing of messages between the various dynos involved in the job. In addition, if decomposition is not done well, the resulting load imbalance leads to additional delays.

Luckily, Gromacs provides users a time-accounting tool to keep track of all these factors. To use it, simply open the “job-name”.log file with a text editor:


The time unit here is in CPU seconds. You can calculate the real time spent on each part of the job by dividing this value by the number of dynos involved, which, in this case, is four dynos. Domain decomposition, waiting, communication, and reading/writing are some of the factors that stop us from achieving ideal scaling. However, advanced users can use the data provided by Gromacs to learn from inefficient runs and design more efficient parallelizations.

If you want to learn more about Gromacs on Rescale, contact us at

This article was written by Rescale.


Gerris is an open-source CFD software tool developed by Dr. Stéphane Popinet of the National Institute of Water and Atmospheric research (NIWA) in New Zealand. While originally developed for modeling complex wind patterns, the code has been used across the world to model complex flows such as spacecraft re-entry dynamics, drag on aircraft airfoils and fuel injections in car and rocket engines.

As part of Rescale’s continuing efforts to support all of the tools that our customers need, we have added Gerris to our library of available software. To demonstrate the utility of the Gerris tool, we ran a simple flow visualization and created a tutorial. This example simulation is a CFD analysis of 2D viscous flow around a heated cylinder.


Initial Setup and Formation of Vortex Tail

This simulation outputs a series of images showing how vortices develop behind the cylinder as time passes. The resulting pattern of alternating vortices is known as a Bénard–von Kárman vortex street.


Run 1 with r=0.06 (Above) and Run 9 with r=0.1 (Below)

Next, we used this simulation to study the effect that changing the diameter of the cylinder may have on the turbulence caused. To do this, we ran a parallel process DoE to evaluate a range of diameters ranging from 0.06 to 0.1 in increments of 0.005 length units.

Run 1 (Top) is a cylinder with a radius of 0.06, and Run 9 (Bottom) is a cylinder of radius 0.1. Apart from the change in radius, both cases have the same initial conditions. These two images also represent the same step in the simulation. In the case with the larger cylinder, the Bénard-Von Kármán Vortex Street is less uniform due to the increase in the size of the vortices formed.

If you want to learn more about Gerris, Gerris has a number of tutorials and examples at its website that are great tools for a first time Gerris user. Those tutorials can be found here:

You can complete this Gerris tutorial here:

If you have any other questions, please contact us at

This article was written by Rescale.