Tag Archives: GTX 1060

Folding@Home on Turing (NVidia GTX 1660 Super and GTX 1650 Combined Review)

Hey everyone. Sorry for the long delay (I have been working on another writing project, more on that later…). Recently I got a pair of new graphics cards based on Nvidia’s new Turing architecture. This has been advertised as being more efficient than the outgoing Pascal architecture, and is the basis of the popular RTX series Geforce cards (2060, 2070, 2080, etc). It’s time to see how well they do some charitable computing, running the now world-famous disease research distributed computing project Folding@Home.

Since those RTX cards with their ray-tracing cores (which does nothing for Folding) are so expensive, I opted to start testing with two lower-end models: the GeForce GTX 1660 Super and the GeForce GTX 1650.

 

These are really tiny cards, and should be perfect for some low-power consumption summertime folding. Also, today is the first time I’ve tested anything from Zotac (the 1650). The 1660 super is from EVGA.

GPU Specifications

Here’s a quick table I threw together comparing these latest Turing-based GTX 16xx series cards to the older Pascal lineup.

Turing GPU Specs

It should be immediately apparent that these are very low power cards. The GTX 1650 has a design power of only 75 watts, and doesn’t even need a supplemental PCI-Express power cable. The GTX 1660 Super also has a very low power rating at 125 Watts. Due to their small size and power requirements, these cards are good options for small form factor PCs with non-gaming oriented power supplies.

Test Setup

Testing was done in Windows 10 using Folding@Home Client version 7.5.1. The Nvidia Graphics Card driver version was 445.87. All power measurements were made at the wall (measuring total system power consumption) with my trusty P3 Kill-A-Watt Power Meter. Performance numbers in terms of Points Per Day (PPD) were estimated from the client during individual work units. This is a departure from my normal PPD metric (averaging the time-history results reported by Folding@Home’s servers), but was necessary due to the recent lack of work units caused by the surge in F@H users due to COVID-19.

Note: This will likely be the last test I do with my aging AMD FX-8320e based desktop, since the motherboard only supports PCI Express 2.0. That is not a problem for the cards tested here, but Folding@Home on very fast modern cards (such as the GTX 2080 Ti) shows a modest slowdown if the cards are limited by PCI Express 2.0 x16 (around 10%). Thus, in the next article, expect to see a new benchmark machine!

System Specs:

  • CPU: AMD FX-8320e
  • Mainboard : Gigabyte GA-880GMA-USB3
  • GPU: EVGA 1080 Ti (Reference Design)
  • Ram: 16 GB DDR3L (low voltage)
  • Power Supply: Seasonic X-650 80+ Gold
  • Drives: 1x SSD, 2 x 7200 RPM HDDs, Blu-Ray Burner
  • Fans: 1x CPU, 2 x 120 mm intake, 1 x 120 mm exhaust, 1 x 80 mm exhaust
  • OS: Win10 64 bit

Goal of the Testing

For those of you who have been following along, you know that the point of this blog is to determine not only which hardware configurations can fight the most cancer (or coronavirus), but to determine how to do the most science with the least amount of electrical power. This is important. Just because we have all these diseases (and computers to combat them with) doesn’t mean we should kill the planet by sucking down untold gigawatts of electricity.

To that end, I will be reporting the following:

Net Worth of Science Performed: Points Per Day (PPD)

System Power Consumption (Watts)

Folding Efficiency (PPD/Watt)

As a side-note, I used MSI afterburner to reduce the GPU Power Limit of the GTX 1660 Super and GTX 1650 to the minimum allowed by the driver / board vendor (in this case, 56% for the 1660 and 50% for the 1650). This is because my previous testing, plus the results of various people in the Folding@Home forums and all over, have shown that by reducing the power cap on the card, you can get an efficiency boost. Let’s see if that holds true for the Turing architecture!

Performance

The following plots show the two new Turing architecture cards relative to everything else I have tested. As can be seen, these little cards punch well above their weight class, with the GTX 1660 Super and GTX 1650 giving the 1070 Ti and 1060 a run for their money. Also, the power throttling applied to the cards did reduce raw PPD, but not by too much.

Nvidia GTX 1650 and 1660 performance

Power Draw

This is the plot where I was most impressed. In the summer, any Folding@Home I do directly competes with the air conditioning. Running big graphics cards, like the 1080 Ti, causes not only my power bill to go crazy due to my computer, but also due to the increased air conditioning required.

Thus, for people in hot climates, extra consideration should be given to the overall power consumption of your Folding@Home computer. With the GTX 1660 running in reduced power mode, I was able to get a total system power consumption of just over 150 watts while still making over 500K PPD! That’s not half bad. On the super low power end, I was able to beat the GTX 1050’s power consumption level…getting my beastly FX-8320e 8-core rig to draw 125 watts total while folding was quite a feat. The best thing was that it still made almost 300K PPD, which is well above last generations small cards.

Nvidia GTX 1650 and 1660 Power Consumption

Efficiency

This is my favorite part. How do these low-power Turing cards do on the efficiency scale? This is simply looking at how many PPD you can get per watt of power draw at the wall.

Nvidia GTX 1650 and 1660 Efficiency

And…wow! Just wow. For about $220 new, you can pick up a GTX 1660 Super and be just as efficient than the previous generation’s top card (GTX 1080 Ti), which still goes for $400-500 used on eBay. Sure the 1660 Super won’t be as good of a gaming card, and it  makes only about 2/3’s the PPD as the 1080 Ti, but on an energy efficiency metric it holds its own.

The GTX 1650 did pretty good as well, coming in somewhere towards the middle of the pack. It is still much more efficient than the similar market segment cards of the previous generation (GTX 1050), but it is overall hampered by not being able to return work units as quickly to the scientists, who prioritize fast work with bonus points (Quick Return Bonus).

Conclusion

NVIDIA’s entry-level Turing architecture graphics cards perform very well in Folding@Home, both from a performance and an efficiency standpoint. They offer significant gains relative to legacy cards, and can be a good option for a budget Folding@Home build.

Join My Team!

Interested in fighting COVID-19, Cancer, Alzheimer’s, Parkinson’s, and many other diseases with your computer? Please consider downloading Folding@Home and joining Team Nuclear Wessels (54345). See my tutorial here.

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