In the last article, I made the statement that running Stanford’s Folding@home distributed computing project on CPUs is a planet-killing waste of electricity. Well, perhaps I didn’t say it in such harsh terms, but that was basically the point. Graphics cards, which are massively multi-threaded by design, offer much more computational power for molecular dynamics solutions than traditional desktop processors. More importantly, they do more science per watt of electricity consumed.
If you’ve been following along, you’ve probably noticed that the processors I’ve been playing around with are relatively elderly (if you are still using a Core2 anything, you might consider upgrading). In this article, I’m going to take a look at a much newer processor, AMD’s Vishera-based 8-core FX-8320e. This processor, circa 2015, is the newest piece of hardware I currently have (although as promised in the previous article, I’ve got a brand new graphics card on the way). The 8-core FX-8320e is a bit of a departure for AMD in terms of power consumption. While many of their high end processors are creeping north of 125 watts in TDP, this model sips a relatively modest (for an 8-core) 95 watts of power. As shown previously here, with more cores, F@H efficiency increases along with overall performance. The 8320e chip should be no exception.
- Designation: AMD FX-8320e
- Architecture: Vishera
- Socket: AM3+
- Manufacturing Process: 32 nm
- # Cores: 8
- Clock Speed: 3.2 GHz (4.0 Turbo)
- TDP: 95 Watts
Side Note: As many will undoubtedly mention, this processor isn’t really a true 8-core in the sense that each pair of cores shares one Floating Point Unit, whereas an ideal 8-core CPU would have 1 FPU per core. So, it will be interesting to see how this processor does against a true 1 to 1 processor such as the 1100T (six FPUs, reviewed here).
All of my power readings are at the plug, so the host system plays a part in the overall efficiency numbers reported. Here is the configuration of my current test computer, for reference:
Test Setup Specs:
- CPU: AMD FX-8320e
- Mainboard : Gigabyte GA-880GMA-USB3
- GPU: Sapphire Radeon 7970 HD
- 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: Win7 64 bit
Since I’ve been out of CPU folding for a while, I had to run through 10 CPU work units in order to be eligible to start getting Stanford’s quick return bonus (extra points received for doing very fast science). You can see the three regions on the plot. The first region is GPU-only folding on the 7970. The second region is CPU-only folding on the FX-8320e prior to the bonus points being awarded. The third region is CPU-only folding with QRB bonus points. Credit for the graph goes to http://folding.extremeoverclocking.com/.
The 8-core AMD chip averages about 20K PPD when doing science on the older A4 core. Stanford’s latest A7 core, which supports Advanced Vector Extensions, returns about 30K PPD on the processor. In either case, this is well short of the 150K PPD on the graphics card, which is also about three years older than the CPU! Clearly, if your goal is doing the most science, the high-end graphics card trumps the processor. (Update note: Intel’s latest processors such as the 6900X have been shown to return in excess of 120K PPD on the A7 core. This makes CPUs relevant again for folding, but not as relevant as modern high-end graphics cards, which can return up to a million PPD! I’ll have more articles on these later, I think…)
I used both HFM.net and the local V7 client to obtain an estimated PPD for the A7 core work unit, which should represent about the highest PPD achievable on the FX-8320e in stock trim.
According to the watt meter, my system is drawing about 160 watts from the wall. So, 29534 PPD / 160 watts is 185 PPD/Watt. Here’s how this stacks up with the hardware tested so far.
Even though the Radeon HD 7970 was released 3 years earlier than AMD’s flagship line of 8-core processors, it still trounces the CPU in terms of Folding@home performance. Efficiency plots show the same story. If you are interested in turning electricity into disease research, you’d be better off using a high-end graphics card than a high-end processor. I hope to be able to illustrate this with higher end, modern hardware in the future.
As a side note, the FX-8320e is the most efficient folder of the processors tested so far. Although not half as fast as the latest Intel offerings, it has performed well for me as a general multi-tasking processor. Now, if only I could get my hands on a new CPU, such as a Kaby Lake or a Ryzen (any one want to donate one to the cause?)…
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