As some of you probably know, being a one-person IT department can be a blessing and a curse. For me, it means being a jack of many trades and master of woefully few. Suffice it to say that I try, but that it can be difficult to keep up with everything. One part of the job that I had to concede to others years ago was building my users’ PCs. Nowadays, almost everyone is content with a laptop and calls for a desktop are few and far between.
Every once in a while, though, there’s a need for something special. When those needs come along, I can’t resist the call to build them myself. I mean, how else are you going to get exactly what you want? You’re not going to get it from Dell, dude. About four years ago, that need led to the assembly and use of “Godzilla”—an Ivy Bridge-E workstation built with PC enthusiast parts. Godzilla had one job: to be a shared resource for translating customer-supplied CAD data from various formats into native SolidWorks data. He worked well enough—for a time.
The user complaints were sporadic at first, but soon coalesced into a clear message. Godzilla, while still very capable, just didn’t cut the mustard anymore. After considering my options and consulting with the rest of the TR staff, I drew up plans for a system that would tackle Godzilla’s weaknesses. “Gipsy Danger” was born.
75% of the cost showed up in the first box from Newegg
Let’s have a look at her specs.
- Intel Core i9-7940X CPU
- G.Skill Trident Z Series 128 GB DDR4 3200 memory
- Asus ROG Strix X299-E Gaming motherboard
- Corsair Hydro Series H115i PRO RGB cooler
- PNY Quadro P4000 NVIDIA Quadro P4000 graphics card
- Samsung 960 EVO M.2 500GB SSD
- Fractal Design Define R6 case
- EVGA SuperNOVA 850 G3 PSU
We’ll talk about those choices more in a moment, but first let’s talk about the logic behind this shared workstation concept and why it leads to building a machine like this. In short, the software is way more expensive than the hardware. As long as my users can play nice together in the same sandbox (which can be a big ask), it’s vastly more cost-effective to build a $4,500 PC than to buy everyone a seat of our preferred translation tool. Not to mention how asking everybody’s own laptops to crunch the numbers would slow down their day-to-day workflow.
I love it when a plan comes together.
We know that doing all the heavy lifting in one place works best, but 128 GB of RAM—really? Yes, really. The translation work is mostly single-threaded, with some exceptions for complex assemblies of multiple parts that the software can spin off to their own threads. That fact still calls for an Intel chip. Gipsy’s 14-core i9-7940X is faster than Godzilla’s quad-core i7-4820K any way you slice it, but let’s face it, not that much faster per-core. No, Gipsy was built to do more things at the same time than Godzilla, pure and simple. Considering that I’ve seen just two simultaneously processing parts use three-quarters of Godzilla’s 64 GB of memory, the 128 GB that Gipsy sports may actually be a little on the low side. Oh, and I got the 3200 MT/s good stuff because it was on sale.
Ain’t she a beaut?
Beyond what I just explained, there isn’t a lot more to say about the i9-7940X choice. It seemed like more, slightly lower-clocked cores would be pointless considering the memory limitations (I can’t believe I just said that about 128 GB of RAM). When I enabled XMP on the Asus motherboard (eight sticks at 15-15-15-35, baby!) I also disabled Multi-Core Enhancement. While I was testing with Prime95, the CPU parked itself at a steady 3.8 GHz on all 14 cores—nice and safe for a workhorse. Speaking of the motherboard, I choose Asus’ Strix X299-E because it wasn’t too extravagant, had decent looking cooling on the VRMs, and because the memory kit was certified for use with it. So far, so good.
This SSD is forever lost under the massive ROG heatsink.
Sometimes the best compliment you can give something is that it needs no explanation. I feel that’s the case for both the Samsung 960 Evo SSD and the EVGA Supernova PSU. Those things are as solid as they come, and I’ve worked with them before. Similarly, the H115i Pro was an easy choice, and it’s keeping the CPU around 50º C under full load. As for the PNY Quadro P4000, well, sometimes you have to pay the piper. A P1000 series card would probably be sufficient, but it just didn’t feel right not putting something a little higher-end into such a nice rig. This way, I have it. At the very least, I needed something with certified drivers so I could get support from software vendors if needed.
Finally, that brings us to the Define R6. Now, I don’t have a lot of experience building in Fractal cases, so there was a small learning curve. Overall, I can see how it all works now, but I had to put things together and take them apart again more times than I would have liked. There’s clearly a lot of thoughtfulness in the case’s design, and it looks incredible, but I still wish it was a bit taller so my preferred top-mounted radiator location had fewer collision issues. Thankfully, I didn’t need the case’s 3.5″ drive mounts and the radiator mount was removable, avoiding what would have caused a lot of frustration building around the top of the motherboard.
Let’s take a look at some rudimentary performance numbers. At the time of this writing, Gipsy has only been in production for just over 24 hours, so I won’t be making any grand proclamations. However, even just using CPU-Z’s built-in benchmark tells the tale I’d expect to see: somewhere around 20-25% single-threaded performance gain, and over 300% multithreaded. That’s not going to save my users a lot of real-time waiting-around when they need something right now, but all those extra cores allow for many more instances of the translation software to run at the same time without bogging things down. I know, who’da thunk?
The type of parts that use 20–30 GB or more of RAM each don’t come around every day, but when they do, they can take double-digit hours to process. Even with 64 GB of memory, Godzilla wasn’t good for much else while chewing on a couple files like that. Gispy’s 128 GB gives her more flexibility. That big pool of RAM isn’t just for running more large files at once—the system has plenty of extra cores available so that folks with simpler needs can skip the line and get their data converted ASAP. Of course, Godzilla is hardly ready for the scrap heap, and for SolidWorks-only work he’ll make a good sidekick to Gipsy for a long time to come.
I hope you enjoyed this impromptu look at my new favorite computer. Some of you probably noticed the thread about this build that I started earlier in the week. I’ll be circling back to that thread soon with more information about real-world usage and performance of both Gipsy and Godzilla. I’ve got a little rendering face-off to run using PhotoView 360, too. Stay tuned.