General Requirements

Minimum requirements for Ansys Discovery software are as follows:

• 64-bit Intel or AMD system, running Windows 10.
• 8 GB RAM
• A dedicated graphics card with latest drivers and at least 1GB video RAM, capable of supporting OpenGL 4.5 and DirectX 11, or higher. Use of integrated graphics (e.g. Intel HD/IRIS) is not recommended and is not support by the Analyze stage in Discovery. See below for special graphics requirements for ANSYS Discovery Live.
• 3 button mouse

If you have or will obtain in the future 32 or more parallel licenses (HPC Packs or Enterprise Licenses) and have one or more users that need to submit jobs using a higher core count than what is available on current Workstations we tend to recommend servers (or a cluster) and a supported Job Scheduler is required.

OS Platform Support | OS Platform Support – By Application

Ansys products are supported on 64-bit operating systems. Ansys Mechanical Ansys Fluent Most of our customers successfully run Ansys software on Windows 10 on Workstations. See the links above for a complete overview of OS platforms supported.

A Server OS (Windows Server or Red Hat Linux/SUSE Enterprise Linux) will be required in the following circumstances:

• More than 2 Physical CPU Sockets in a System
• Multiple Machines Running in a Cluster
• Simultaneous Users on a Machine (Remote or Local)

The latest 64-bit multi-core Intel Xeon and AMD processors with the highest clockspeed and core counts available are recommended. Hyper threading will not improve the speed of simulations, always evaluate the number of physical cores for Ansys simulation. Always try to get the most recent architecture version of the CPU, even if the clockspeed or number of cores don’t seem to be improved. CPUs today are almost twice as fast as CPUs from 3 years ago listed at the same clockspeed.

Keep in mind that Windows 7/8/10 only support a maximum of two physical CPUs. For more than two physical CPUs, a Windows Server or Linux OS is needed.

A minimum of 16GB of memory is recommended. It is best to have as much memory as financially feasible. The actual memory required for a particular problem will depend on the mesh, physical models that are enabled, and domain complexity. As of 2016, 64GB of memory has been sufficient for 90% of the FEA and CFD projects completed by OEI engineers. EMAG products more often require more memory and 100+GB is recommended.

In terms of the effect of memory on performance, you either have enough or you don’t. If your operating system runs out of memory it will fall back to using the hard drive as ‘virtual’ memory, which will have a catastrophic effect on system performance.

To get an idea why this is, it is useful to consider how the CPU works. CPUs have an extremely small amount of memory that they can access immediately. We’ll call this the register. To access something not already in the register, the CPU will have to wait for the process to bring it into the register to complete before it can continue. There are several levels of memory in ascending size and descending performance that the CPU has access to. The cache levels are directly on the CPU itself and have various levels, termed L1, L2, etc… The system memory, or RAM, is modularly added to the motherboard, as is the hard drive. To compare the proportional speed of these memory levels, we can use the metaphor from this excellent article on the subject:

• L1 Cache: Grabbing a piece of paper from your desk (3 seconds)
• L2 Cache: Picking up a book from a nearby shelf (12 seconds)
• System Memory: Taking a walk down the hall to buy a Twix Bar (4 minutes)
• Accessing the Hard Drive: Leaving the building and roaming the earth for 1 year and 3 months

It doesn’t pay to pinch pennies on system memory!

A minimum of 1TB is recommended for the installation and use of your Ansys software. An efficient approach to storage for Ansys might include:  one smaller & faster drive (NVMe) for solving, and one larger & slower drive (Mechanical, SSD) for storage.  In Ansys Mechanical, you can specify a Solver Scratch Directory to ensure that solutions are automatically performed on high performance drives but stored on general purpose storage.

The precise effect of storage on performance will depend on how I/O bound a particular analysis type is but it is uniformly better as model sizes get larger. Strongly consider one of the advanced storage recommendations below if your expected analysis type is one of the following where I/O is typically a bottleneck on performance:

• Out of core Sparse Solver in Mechanical
• Block Lanczos Eigensolver
• Distributed Memory Parallel (DMP) solves (in SMP, there is one set of files, in DMP each core has its own set of files and IO becomes a bottleneck)
• Transient FEA or CFD runs where many results are being written to disk

There are different ways to increase storage performance:

NVMe: Recently, the NVMe price has reduced and performance has improved.  NVMe (Non-Volatile Memory Express) is the most highly-recommended storage type for high-performance requirements in reading and writing data.

SSDs: Significantly more expensive on a per GB basis than mechanical hard drives but can have 2 orders of magnitude faster read performance and an order of magnitude faster write performance. Make sure to have a modern operating system with TRIM support or the write performance of the SSD will degrade over time.

RAID0: While there are many different RAID configurations that have trade-offs between speed, redundancy and efficient usage of space, RAID0 is the only configuration that should be considered for performance. Redundancy should only be considered for separate ‘storage’ drives or arrays, especially since RAID0 sacrifices redundancy the most for performance (if any of the drives in a RAID0 array fails, all the data is lost).

SSDs + RAID0:  Make sure TRIM is supported specifically for RAID0 with your chosen brand and operating system. The SSD alone supporting TRIM does not mean that it is supported in RAID0 arrays, which is a very recent development that often requires the latest operating system (eg Windows 10) and drivers.

• Supported Graphics CardsFor large assemblies it is recommended to make use of a graphics card to avoid display latency issues. A list of validated graphics cards can be found in the links above.On board graphics will degrade the pre and postprocessing experience on the machine. Additionally, newer and graphically intensive applications such as AIM and SpaceClaim will not work without a discrete graphics card.

GPU Computing Resources | Supported GPU Cards

In an effort to provide faster performance during solution, various Ansys products (Ansys Mechanical & Ansys Fluent) support offloading key solver computations onto graphics cards to accelerate those computations. All HPC license products (HPC, HPC Packs, and HPC Workgroups) enable GPU-accelerated computing and one GPU will count as one core. Note that not all CUDA enabled graphics cards are supported, this feature is intended for the high end NVIDIA Tesla and Intel Phi cards. It is recommended to get the card with the highest amount of memory. The supported cards for GPU computing can be found in the document linked above:

Notes about GPU Computing:

• The NVIDIA Tesla solutions are more feature complete as of 2017. Not all analysis types are supported for GPU computing.
• GPU computing is currently well suited for particular types of problems:
  • Mechanical: In-Core Sparse Solver runs with solid elements (vs shells) of 500k+ degrees of freedom but still able to be contained within the GPU memory (typically <8M DOF)
  • Mechanical: PCG/ICG Solver runs with the Level of Difficulty setting at a lower value and MSAVE off
  • Fluent (& Icepak): Single Phase, flow dominated, coupled solvers, model size > 3-4M elements

HPC Features Overview

To take full advantage of your computer hardware, make sure that you have the appropriate HPC licenses. There are flexible HPC, HPC Pack and HPC Workgroup options. HPC licenses are on a per-core basis. A single GPU is licensed as a single core. The HPC Packs add non-linearly to quickly get to a large amount of cores.

The following specs are an example of a mid-range desktop workstation used by a typical Ansys analyst. Please keep in mind that these systems were configured in 2020 and still perform well using Ansys 2020R1. Other server hardware is available for more demanding tasks.

Chassis: Full size desktop workstation tower

Processor: Intel Xeon/Core or AMD EPYC (preferred specifications per cost – latest architecture, highest clock speed, greatest number cores)

Motherboard: Single processor workstation/server motherboard

Memory: 64GB (low) – 256GB (high) RAM

Storage: 512GB NVMe + 2TB HDD

Operating System: Windows 10 64-bit 

For non-workstation systems feel free to contact us for guidance.