Barracuda Virtual Reactor System Requirements
Virtual Reactor can be used on either Linux or Windows. The following table lists minimum and recommended system requirements.
|Operating System||Recent 64-bit Linux
64-bit Windows 7, 8, or 10
|64-bit CentOS 6 (RHEL 6) or higher
Windows 10 Professional 64-bit
|CPU||Any 64-bit Intel compatible from the last 5 years||Intel Core i7-9800X (4.4 GHz, 8 cores, 16.5 MB cache) or better. Higher clock speed, and newer Intel architecture are better.|
|Memory (RAM)||8 GB||2x as much as your GPU Memory. Faster is better.|
|Hard drive space||500 GB||Boot Drive: 1 TB SSD or M.2 NVMe
Data Drives: 2 x 8 TB 7200 RPM HDDs
|GPU *||NVIDIA GPU required||NVIDIA Titan RTX (24 GB)
NVIDIA Quadro RTX 8000 (48 GB)
We recommend running a single Barracuda calculation per GPU, so if you have more than 1 license of Barracuda, you should buy a GPU for each license
|CUDA Compute Compatibility *||2.0||3.5 or higher|
|GPU RAM *||4 GB||24 GB or more|
* - GPU requirements only apply if Virtual Reactor will be running in GPU parallel mode. The required GPU RAM is also dependent on the size of the simulation being run. A larger simulation will require more GPU RAM.
Though Virtual Reactor simulations can be run on laptops, or lower-performance desktop machines, doing so is generally not recommended. Investing in an up-to-date calculation machine, with the fastest hardware currently available, will provide much faster calculation speeds. Additionally, since computer hardware advances in capacity and speed at such a fast pace, it is recommended to purchase updated hardware every 2 to 3 years to obtain the fastest performance.
Virtual Reactor can be installed on compute nodes of a cluster. However, it will not take advantage of the multi-node parallel computing capabilities of the cluster. Each Virtual Reactor simulation utilizes a single CPU core, and parallelization is available solely through the use of an NVIDIA GPU. Since each individual node of a cluster is not usually optimized for the fastest possible single-core CPU performance, it is often the case that running Virtual Reactor on a cluster node will not give the best possible calculation speed. Instead, it is generally better to purchase a very fast single-CPU standalone calculation machine on which to run Virtual Reactor. This standalone machine will outperform a cluster node in the majority of cases, for the purpose of running Virtual Reactor.