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NVIDIA Maximus Unveiled: A Mini-HPC System in a Desktop Box

NVIDIA launches Maximus, a new class of workstations with enough horsepower to run CAD software, render photo-realistic scenes, and process FEA and CFD jobs -- all at the same time.

Maximus workstations will be powered by not one but two GPUs: a Quadro GPU and a Tesla GPU.

The Quadro GPU and Tesla GPU in Maximus workstations will run on a unified driver, making OEM certification easier.

When you think of a high performance computing (HPC) system, you might envision a series of rack-mounted servers housed in a climate-controlled room. It’s the parallel-processing Goliath that the entire company relies on for heavy-duty simulation jobs, like finite element analysis (FEA) and computational fluid dynamics (CFD). Now, NVIDIA is introducing what amounts to a mini-HPC system inside a workstation — Goliath’s enviable strength in David’s nimble form.

Dual GPU Setup
Packed into a standard workstation, NVIDIA’s Maximus technology is expected to let you work in a CAD modeling program, render photorealistic product shots, and run simulation jobs — all at the same time. Usually, an engineering or design workstation is powered by a multicore CPU and a processional graphics processor (like NVIDIA’s Quadro GPU). In a Maximus machine, however, you get the combined horsepower of a CPU, a Quadro GPU, and a Tesla GPU.

With the ability to dynamically balance computation workload, Maximus workstations are designed to determine and distribute processing jobs to the appropriate processors (for example, delegating interactive CAD modeling to the CPU, OpenGL-powered graphics rendering to Quadro GPU, and CUDA-powered fluid dynamic jobs to Tesla GPU) with little or no intervention from the user.

According to NVIDIA, its hardware partners are on board to begin delivering Maximus workstations equipped with NVIDIA Tesla C2075 GPUs. Earliest units are expected to come from Dell, HP, Lenovo, and Fujitsu. Prices for Maximus workstations are estimated to begin around $8,000 to $10,000.

NVIDIA explains that the Tesla GPU used with Maximus technology is the same ones used for clusters, but its architecture has been slightly modified to fit into a traditional workstation (Tesla units for clusters, for example, use a different cooling technology). To enable easy load balancing and OEM certification, NVIDIA will allow Quadro and Tesla GPUS to run on a unified driver.

Parallel Processing Power for Parallel Design Workflow
In many engineering firms, the HPC system is a monster with a long tail. Because it’s a shared resource used by a pool of engineers and designers, many submitted jobs tend to sit in the system’s queue for a while before they get their turns. The wait, which puts critical design decisions on hold, has become an inevitable part of simulation-driven projects. NVIDIA anticipates that many of these users will look to Maximus workstations’ local HPC-processing power as a way to bring relief to their simulation bottlenecks.

By bringing FEA and CFD processing power back to local machines, NVIDIA offers engineers an ideal multitasking possibility: They can now design their product’s geometry in CAD software, evaluate its aesthetics in near real-time rendering mode, and verify its structural integrity and functions through simulation. Previously, engineers could only perform these tasks one at a time, as rendering and simulation tend to consume all the computing cores available in the machine and slow down the unit to a crawl. But with a Maximus-class workstation, engineers may perform all these tasks in parallel — without suffering from a system slowdown or software performance degradation.

For more, read my guest blog post at NVIDIA’s blog and listen to a recorded Q&A with David Watters, NVIDIA’s senior director of marketing for manufacturing and design segments.


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About Kenneth

Kenneth Wong has been a regular contributor to the CAD industry press since 2000, first an an editor, later as a columnist and freelance writer for various publications. During his nine-year tenure, he has closely followed the migration from 2D to 3D, the growth of PLM (product lifecycle management), and the impact of globalization on manufacturing. His writings have appeared in Cadalyst, Computer Graphics World, and Manufacturing Business Technology, among others.


  1. Maximus: will I loose the compute power of my quadro if use an additional Tesla??

    There is one important question:
    will the quadro be automatically used for cuda calculation if there is no strong graphic load on it?
    Or do I loose its compute power completely if I put in an additional Tesla??

    if it could be used for computing together with the new tesla: What happens if graphic load increase?
    will there be a smooth transition? eg
    Tesla: compute load 100% , graphic load 0%
    Quadro: compute load 30%, graphic load 70%

    Best regards HPVD

  2. hpvd: I have not tested the hardware, so I’m only reporting from my briefing. I was told that, if the Tesla compute load is maxed out and Quadro is free, dynamic load balancing will use the available cores in Quadro to augment Tesla’s processing. In a Maximus machine, Quadro will most likely be delegated to displaying real-time (or near real-time) rendered views of your CAD model. (So if you’re using CATIA, for instance, you can work in a fully rendered mode interactively as you edit your design’s geometry). At the same time, you may also be using Tesla to run SIMULIA jobs in the background.

  3. NVIDIA is doing everything it can to make TESLA applicable to CAE, but the real holdback to its widespread adoption is that the commercial CAE provider companies have not brought out versions runable with TESLA (except for ANSYS, according to the DE reporting I have read so far). The forging simulator our company uses has no plans to support TESLA (their rep hadn’t even heard of it).

  4. Dave: Good point! Thanks for sharing your thoughts. Some household names in CAE may be investing in making their software run on Tesla. Dassault Systemes’ SIMULIA is among them.


    But I agree that, currently, many CAE software developers are still trying to figure out how to code (or recode) their software to take advantage of parallel processing on GPU.


  5. i want to learn and using this Product , please tell me

  6. A rack server, also called a rack-mounted server, is a computer dedicated to use as a server and designed to be installed in a framework called a rack. Rack company should be the leading Server Racks manufacturers and supplier, should be known for providing best in class server racks.

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