Modena Computers Hydra vs Hydra XL

We recently launched our Hydra XL Workstation, which has the capacity for some crazy specs. It allows for 2 CPUs, 4 GPUs, and up to 2TB RAM.

This is considered a step up from our standard Hydra Workstation, but it’s not always the ideal choice for the job. There are some very specific use-cases for both machines, and in this article, we’ll discuss their recommended applications.

Maximum Specs

First of all, let’s take a look at the maximum capacity of each system.

 

Hydra

Hydra XL

CPU Cores

64

128

RAM

256GB

2TB

GPUs

2

4

As you can see, there’s a lot more that fits into a Hydra XL, but not everyone will be able to make use of those kinds of specs.

In any application, there comes a point of diminishing returns – once you have enough cores, RAM, and graphics processing power, adding on more won’t give you any noticeable gain in performance or user experience.

HYDRA

Here are some of the optimal use cases for the standard Hydra:

Video Editing

Programs like DaVinci Resolve are able to scale very well with pretty much everything. More CPUs, higher CPU frequencies, more GPU power, and more RAM all allow for faster rendering at higher resolutions.

A Threadripper 3990X with 256GB RAM and 2 x RTX 3090 24GB graphics cards would provide incredible performance in this kind of program.

The other benefit Threadripper has over the consumer grade Ryzen platform is the amount of PCIe lanes. Many users of DaVinci Resolve like to use Blackmagic PCIe cards to edit in higher resolutions in real-time. Since Threadripper has more lanes than Ryzen, it is able to handle 2 GPUs and multiple PCIe SSDs, in addition to the Blackmagic card, while a Ryzen system would be much more limited in this regard.  

Point Cloud Processing

Faro Scene is a common option when working with point clouds. This software requires a good balance of CPU cores and frequency, which makes the standard Hydra a better option than the Hydra XL, which doesn’t quite reach the same speeds.

It also requires a lot of RAM to load up larger projects. The Hydra has the capacity for both more RAM and more cores than our Vulcan systems, which is another reason that this is the optimal solution for this kind of work.  

Other tasks

There are some tasks that can be handled very well by our Vulcan systems, but could still benefit from a Hydra. FEA and rendering are some examples of this, especially when working on larger projects. There comes a point when 128GB RAM is simply not enough, likewise for 32 CPU cores.

Depending on your particular budget and workflow, we may recommend stepping up to this platform.

HYDRA XL

There are some tasks that really do need as much RAM or as many cores as possible.

Virtual Machine Server

Servers need to be able to handle a lot of data all at once, and 2TB RAM is not uncommon in this kind of setup.

With the high core count and the option for multiple Quadro graphics cards, it’s also possible to run a large number of virtual machines all at once. This is possible by splitting the CPU cores, RAM, and GPU VRAM between the VMs.

For example, a system with a Threadripper Pro 3995WX, 1TB RAM, and 4 x RTX A5000 GPUs, it becomes possible to run 16 virtual machines, each with 4 cores, 64GB RAM, and 6GB VRAM.

Computational Fluid Dynamics

Programs like DaVinci Resolve are able to scale very well with pretty much everything. More CPUs, higher CPU frequencies, more GPU power, and more RAM all allow for faster rendering at higher resolutions.

A Threadripper 3990X with 256GB RAM and 2 x RTX 3090 24GB graphics cards would provide incredible performance in this kind of program.

The other benefit Threadripper has over the consumer grade Ryzen platform is the amount of PCIe lanes. Many users of DaVinci Resolve like to use Blackmagic PCIe cards to edit in higher resolutions in real-time. Since Threadripper has more lanes than Ryzen, it is able to handle 2 GPUs and multiple PCIe SSDs, in addition to the Blackmagic card, while a Ryzen system would be much more limited in this regard.  

Machine Learning

TensorFlow is a common tool for machine learning professionals. Because GPUs are made up of a large number of small cores, they are able to process the relevant data a lot faster than would be possible using only CPU power.

What this means is that multiple GPUs can be very effective for this kind of work. Since the Hydra XL has enough room for 4 GPUs, this kind of system would allow for the highest performance possible in this kind of application.

Noctua

Conclusion

In summary, the Hydra and Hydra XL both represent the ultimate performance within their respective categories. 

Whether you need one or the other depends on you – your personal workflow and budget. 

Whichever you may be looking for, we’d love to help you put together the absolute best workstation for you, so please do not hesitate to contact us for a personalised proposal.

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