Maximizing Ansys Performance: 5 Considerations for Building Effective Cloud Instances 

Building a high performance computing cluster for your specific needs used to be easier said than done, but we’re making strides to change that. With organizations needing their own HPC and big data systems now more than ever before, it’s important that the process of identifying what kind of system you need be as simple as possible, especially those in the engineering space that are working day after day to solve the world’s problems. This means that engineering organizations, particularly Ansys users, need systems that are designed to run exactly as they need them to, for their unique purposes. Here are five things Ansys users should consider when configuring a custom HPC cluster:

Analyzing User Needs

How many users? What type of jobs will they be running? Are some users priority over others? Being able to set user expectations on utilization of the system cannot be overstated. If you have hundreds of users, then be sure to budget and build a machine that can easily meet this demand. If some users have higher priority than others, make sure this information is available to the manufacturer, as the job scheduler will need to be setup and configured correctly.

Technical Capability of Users

Are all users comfortable with a consolidated HPC environment? Are they mostly Windows or Linux? Will there be a dedicated systems administrator? The answers to these questions will have a direct impact on the direction you take when it comes to choosing the right HPC cluster vendor.

HPC Instances

Most Ansys users typically require a fair amount of computing power. This means that selecting the right number of cores, memory and high speed network backplane is critical to a successful deployment. We’ve found that fewer cores per node paired with a higher clock speed is typical because of the way that Ansys licenses their software applications. AMD EPYC CPUs offer a significant jump in GHz speed per core, while still maintaining reasonable cost.

With the minimum amount of memory being 2 GB memory per processor core, and Ansys users tending to use 6 GB memory per core or more, it’s important that memory configuration be optimized for maximum bandwidth.

Additionally, one node should be dedicated to visualization. Be sure to include a NVIDIA Quadro GPU in the “Head Node” or dedicated “Viz Node” to meet this need.

Determining Budget

In order to maximize your budget, this needs to be determined as early as possible. Establishing budget early on means that you are able to prioritize which components of your system are most important. If you need a machine with thousands of cores, but are operating under a limited budget, your vendor can help you identify trade-offs within the system that can make this possible.

Selecting Vendor

There are many options when it comes to selecting an HPC vendor, from cloud providers to Tier 1s to smaller, specialized HPC manufacturers. For users that just need to run a jump or two once in a while, cloud resources may be enough. But often times, these same users reach a certain usage level that makes the cost of cloud computing unreasonably high, and that usage level threshold is often much lower than users anticipate.

Nearly all cost calculators will eventually point you in the direction of purchasing a dedicated piece of hardware if you accurately account for the workloads you’ll be running on your cluster. In fact, most buyers find that the cost of buying a dedicated HPC cluster pays for itself when compared to 6-8 months of consistent cloud-usage. This means that most Ansys users end up turning away from cloud computing options during this discovery phase, and rightfully so. They then begin comparing the trade-offs of working with a Tier 1 manufacturer versus a company that specializes in delivering HPC clusters to Ansys end users.

With years of experience providing high performance computing clusters to Ansys end users, our engineers here at NZO CLOUD listen to the specific needs of our clients and then work with them to customize a solution, within any time and budgetary constraints. Our Private Cloud + HPC Instances is the cluster that many of our Ansys users end up purchasing, and for good reason – it’s application-optimized, scalable, and delivered production ready.

All in all, there are several things to consider when selecting or building a custom HPC cluster. That’s why it’s even more important to work with the right partner – one that can listen to your unique business needs and help you build a system that will perform exactly as you need it to, without the sky high costs of Tier 1 manufacturers.