Harnessing the Power of the Cloud: Running RS3 Models Faster Than Ever
- Jim Zhao, Software Developer at Rocscience
- Kien Dang, FE Group Manager at Rocscience
At Rocscience’s core, is our desire to innovate and develop features that will improve the user experience of our programs. One of our latest developments will deliver on this promise by allowing RS3 models to be run on the cloud.
What benefits does the Cloud offer RS3 users?
RS3 models can often be large and detailed, and as a result be time consuming to run. This is why powerful computer hardware is always recommended to speed up the process, however, this hardware comes at a cost. Even with powerful on-premises machines, could cloud computing offer a method to further improve the speed of running of RS3 models?
RS3 & Cloud Computing
We have created a platform in the cloud that runs RS3 engine models to drastically reduce computation time.
The two main benefits of leveraging the Cloud for computing RS3 models:
- Performance Improvements: Leveraging AWS’s powerful servers with Intel Xeon Processors and up to 512 GB of RAM, we have seen performance gains of 1.5-3x compared to some extremely powerful desktop machines. Since the Cloud also has a huge pool of machines, multiple models could be run simultaneously if desired.
- Convenience: You don’t have to purchase and maintain powerful hardware to run your RS3 models. Simply upload your compute file and the Cloud will take care of the rest.
Performance Improvements of the Cloud
To highlight the performance improvements of the cloud for RS3 computations, a test model was run with 2,383,317 elements and 9,737,631 degrees of freedom. This test compared the run time of on-premises machines with cloud virtual machines (VMs).
The results for the on-premises machines were:
Machine Type |
Processor |
Cores | Memory |
Run Time |
Dell XPS 15 9500 |
Intel I7-10875H |
8 | 64 GB |
9hrs, 37mins, 57secs |
Dell XPS 8950 |
Intel i9-12900K |
16 | 128 GB |
5hrs, 52mins, 30secs |
Custom |
Intel i9-10980XE |
18 | 256 GB |
4hrs, 39mins, 15secs |
The results for cloud VMs were:
Machine Type |
Processor |
Cores | Memory |
Run Time |
r6i.2xlarge |
Intel Xeon 8375C |
8 | 64 GB |
6hrs, 10mins, 7secs |
m6i.4xlarge |
Intel Xeon 8375C |
16 | 64 GB |
5hrs, 35mins, 1sec |
r6i.8xlarge |
Intel Xeon 8375C |
32 | 256 GB |
3hrs, 2mins, 13secs |
As you can see, one of the cloud machines ran the model in just over 3 hours, which was:
- 1.5x faster than the custom desktop machine
- 2x faster than the Dell XPS 8950, a powerful desktop machine
- 3x faster than the Dell XPS 15 9500, a powerful laptop machine
The future of the Cloud for Geotechnical Analysis
This development showcases the power that cloud computing functionality can bring to the Rocscience software ecosystem. We will be starting to test out this functionality with RS3 users as 3D FEM analysis stands to gain the most from this technology, however, the possibilities are endless, and this capability could be extended to other programs in the future.
Are you an RS3 user that is interested in leveraging cloud computing for your models? If you have got a large model and would like to see if this functionality could help speed up your analysis, contact us here, and we would be happy to talk with you.