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We engineered a game-changing low-cost supercomputer configuration that reduces the HPC purchase cost by 2/3 to 3/4. The solution is a good fit for nearly all, but not all organizations.

For over a decade, the technology community has been aware that consumer grade GPUs perform as well, and in some cases better than commercial grade GPUs at a price that is anywhere from 2/3 to 3/4 less. The main sticking point has been the traditional supercomputer chassis configuration, which only accommodates the significantly more expensive commercial grade GPUs. This puts GPU supercomputers out of the price range of many organizations—including some research institutions that need extraordinary processing power, but have budget constraints.

We worked with top sheet metal engineers that had experience with computer cases to redesign the traditional supercomputer chassis so that it can accommodate consumer-grade GPUs. Then our engineers solved integration complexities.

It’s important to note that, while this is new for the supercomputer community, it is not new for us or our clients—some of the largest research institutions in the world have been using this Nor-Tech design for more than five years with almost no issues.

While this is an excellent solution for most organizations, it’s not for everyone. The only compromise in performance is occasional bit error.  Good candidates are organizations that need supercomputing capabilities for trending and averaging—not organizations that require ECC memory or double precision math.Will consumer grade GPUs work in a cluster?

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