Tag Archives: Efficiency

Nvidia GeForce GTX 1070 Ti Folding@Home Review

In an effort to make as much use of the colder months in New England as I can, I’m running tons of Stanford University’s Folding@Home on my computer to do charitable science for disease research while heating my house. In the last article, I reviewed a slightly older AMD card, the RX 480, to determine its performance and efficiency running Folding@Home. Today, I’ll be taking a look at one of the favorite cards from Nvidia for both folding and gaming: The 1070 Ti.

The GeForce GTX 1070 Ti was released in November 2017, and sits between the 1070 and 1080 in terms of raw performance. As of February 2019, the 1070 Ti can be for a deep discount on the used market, now that the RTX 20xx series cards have been released. I got my Asus version on eBay for $250.

Based on Nvidia’s 14nm Pascal architecture, the 1070 Ti has 2432 CUDA cores and 8 GB of GDDR5 memory, with a memory bandwidth of 256 GB/s. The base clock rate of the GPU is 1607 MHz, although the cards automatically boost well past the advertised boost clock of 1683 Mhz. Thermal Design Power (TDP) is 180 Watts.

The 3rd party Asus card I got is nothing special. It appears to be a dual-slot reference design, and uses a blower cooler to exhaust hot air out the back of the case. It requires one supplemental 8-pin PCI-E Power connection.


ASUS GeForce GTX 1070 Ti

One thing I will note about this card is it’s length. At 10.5 inches (which is similar to many NVidia high-end cards), it can be a bit problematic to fit in some cases. I have a Raidmax Sagitta mid-tower case from way back in 2006, and it fits, but barely. I had the same problem with the EVGA GeForce 1070 I reviewed earlier.


ASUS GTX 1070 Ti – Installed.

Test Environment

Testing was done in Windows 10 on my AMD FX-based system, which is old but holds pretty well, all things considered. You can read more on that here. The system was built for both performance and efficiency, using AMD’s 8320e processor (a bit less power hungry than the other 8-core FX processors), a Seasonic 650 80+ Gold Power Supply, and 8 GB of low voltage DDR3 memory. The real key here, since I take all my power measurements at the wall with a P3 Kill-A-Watt meter, is that the system is the same for all of my tests.

The Folding@Home Client version is 7.5.1, running a single GPU slot with the following settings:

GPU Slot Options

GPU Slot Options for Maximum PPD

These settings tend to result in a slighter higher points per day (PPD), because they request large, advanced work units from Stanford.

Initial Test Results

Initial testing was done on one of the oldest drivers I could find to support the 1070 Ti (driver version 388.13). The thought here was that older drivers would have less gaming optimizations, which tend to hurt performance for compute jobs (unlike AMD, Nvidia doesn’t include a compute mode in their graphics driver settings).

Unfortunately, the best Nvidia driver for the non-Ti GTX 10xx cards (372.90) doesn’t work with the 1070 Ti, because the Ti version came out a few months later than the original cards. So, I was stuck with version 388.13.

Nvidia 1070 TI Baseline Clocks

Nvidia GTX 1070 Ti Monitoring – Baseline Clocks

I ran F@H for three days using the stock clock rate of 1823 MHz core, with the memory at 3802 MHz. Similar to what I found when testing the 1070, Folding@Home does not trigger the card to go into the high power (max performance) P0 state. Instead, it is stuck in the power-saving P2 state, so the core and memory clocks do not boost.

The PPD average for three days when folding at this rate was 632,380 PPD. Checking the Kill-A-Watt meter over the course of those days showed an approximate average system power consumption of 220 watts. Interestingly, this is less power draw than the GTX 1070 (which used 227 watts, although that was with overclocking + the more efficient 372.90 driver). The PPD average was also less than the GTX 1070, which had done about 640,000 PPD. Initial efficiency, in PPD/Watt, was thus 2875 (compared to the GTX 1070’s 2820 PPD/Watt).

The lower power consumption number and lower PPD performance score were a bit surprising, since the GTX 1070 TI has 512 more CUDA cores than the GTX 1070. However, in my previous review of the 1070, I had done a lot of optimization work, both with overclocking and with driver tuning. So, now it was time to do the same to the 1070 Ti.

Tuning the Card

By running UNIGINE’s Heaven video game benchmark in windowed mode, I was able to watch what the card did in MSI afterburner. The core clock boosted up to 1860 MHz (a modest increase from the 1823 base clock), and the memory went up to 4000 MHz (the default). I tried these overclocking settings and saw only a modest increase in PPD numbers. So, I decided to push it further, despite the Asus card having only a reference-style blower cooler. From my 1070 review, I found I was able to fold nice and stable with a core clock of 2012 MHz and a memory clock of 3802 MHz. So, I set up the GTX 1070 Ti with those same settings. After running it for five days, I pushed the core a little higher to 2050 Mhz. A few days later, I upgraded the driver to the latest (417.71).

Nvidia 1070 TI OC

Nvidia GTX 1070 Ti Monitoring – Overclocked

With these settings, I did have to increase the fan speed to keep the card below 70 degrees Celsius. Since the Asus card uses a blower cooler, it was a bit loud, but nothing too crazy. Open-air coolers with lots of heat pipes and multiple fans would probably let me push the card higher, but from what I’d read, people start running into stability problems at core clocks over 2100 Mhz. Since the goal of Folding@home is to produce reliable science to help Stanford University fight disease, I didn’t want to risk dropping a work unit due to an unstable overclock.

Here’s the production vs. time history from Stanford’s servers, courtesy of https://folding.extremeoverclocking.com/

Nvidia GTX 1070 Ti Time History

Nvidia GTX1070 Ti Folding@Home Production Time History

As you can see below, the overclock helped improve the performance of the GTX 1070 Ti. Using the last five days worth of data points (which has the graphics driver set to 417.71 and the 2050 MHz core overclock), I got an average PPD of 703,371 PPD with a power consumption at the wall of 225 Watts. This gives an overall system efficiency of 3126 PPD/Watt.

Finally, these results are starting to make more sense. Now, this card is outpacing the GTX 1070 in terms of both PPD and energy efficiency. However, the gain in performance isn’t enough to confidently say the card is doing better, since there is typically a +/- 10% PPD difference depending on what work unit the computer receives. This is clear from the amount of variability, or “hash”, in the time history plot.

Interestingly, the GTX 1070 Ti it is still using about the same amount of power as the base model GTX 1070, which has a Thermal Design Power of 150 Watts, compared to the GTX 1070 Ti’s TDP of 180 Watts. So, why isn’t my system consuming 30 watts more at the wall than it did when equipped with the base 1070?

I suspect the issue here is that the drivers available for the 1070 Ti are not as good for folding as the 372.90 driver for the non-Ti 10-series Nvidia cards. As you can see from the MSI Afterburner screen shots above, GPU Usage on the GTX 1070 Ti during folding hovers in the 80-90% range, which is lower than the 85-93% range seen when using the non-Ti GTX 1070. In short, folding on the 1070 Ti seems to be a bit handicapped by the drivers available in Windows.

Comparison to Similar Cards

Here are the Production and Efficiency Plots for comparison to other cards I’ve tested.

GTX 1070 Ti Performance Comparison

GTX 1070 Ti Performance Comparison

GTX 1070 Ti Efficiency Comparison

GTX 1070 Ti Efficiency Comparison


The Nvidia GTX 1070 Ti is a very good graphics card for running Folding@Home. With an average PPD of 703K and a system efficiency of 3126 PPD/Watt, it is the fastest and most efficient graphics card I’ve tested so far. As far as maximizing the amount of science done per electricity consumed, this card continues the trend…higher-end video cards are more efficient, despite the increased power draw.

One side note about the GTX 1070 Ti is that the drivers don’t seem as optimized as they could be. This is a known problem for running Folding@Home in Windows. But, since the proven Nvidia driver 372.90 is not available for the Ti-flavor of the 1070, the hit here is more than normal. On the used market in 2019, you can get a GTX 1070 for $200 on ebay, whereas the GTX 1070 Ti’s go for $250. My opinion is that if you’re going to fold in Windows, a tuned GTX 1070 running the 372.90 driver is the way to go.

Future Work

To fully unlock the capability of the GTX 1070 Ti, I realized I’m going to have to switch operating systems. Stay tuned for a follow-up article in Linux.


Folding on the NVidia GTX 1060


Folding@home is Stanford University’s charitable distributed computing project. It’s charitable because you can donate electricity, as converted into work through your home computer, to fight cancer, Alzheimer, and a host of other diseases.  It’s distributed, because anyone can run it with almost any desktop PC hardware.  But, not all hardware configurations are created equally.  If you’ve been following along, you know the point of this blog is to do the most work for as little power consumption as possible.  After all, electricity isn’t free, and killing the planet to cure cancer isn’t a very good trade-off.

Today we’re testing out Folding@home on EVGA’s single-fan version of the NVIDIA GTX 1060 graphics card.  This is an impressive little card in that it offers a lot of gaming performance in a small package.  This is a very popular graphics card for gamers who don’t want to spend $400+ on GTX 1070s and 1080s.  But, how well does it fold?

Card Specifications

Manufacturer:  EVGA
Model #:  06G-P4-6163
Model Name: EVGA GeForce GTX 1060 SC GAMING (Single Fan)
Max TDP: 120 Watts
Power:  1 x PCI Express 6-pin
GPU: 1280 CUDA Cores @ 1607 MHz (Boost Clock of 1835 MHz)
Memory: 6 GB GDDR5
Bus: PCI-Express X16 3.0
MSRP: $269


EVGA Nvidia GeForce GTX 1060 (photo by EVGA)

Folding@Home Test Setup

For this test I used my normal desktop computer as the benchmark machine.  Testing was done using Stanford’s V7 client on Windows 7 64-bit running FAH Core 21 work units.  The video driver version used was 381.65.  All power consumption measurements were taken at the wall and are thus full system power consumption numbers.

If you’re interested in reading about the hardware configuration of my test rig, it is summarized in this post:


Information on my watt meter readings can be found here:

I Got a New Watt Meter!


The Nvidia GTX 1060 delivers the best Folding@Home performance and efficiency of all the hardware I’ve tested so far.  As seen in the screen shot below, the native F@H client has shown up to 330K PPD.  I ran the card for over a week and averaged the results as reported to Stanford to come up with the nominal 305K Points Per Day number.  I’m going to use 305 K PPD in the charts in order to be conservative.  The power draw at the wall was 185 watts, which is very reasonable, especially considering this graphics card is in an 8-core gaming rig with 16 GB of ram.  This results in a F@H efficiency of about 1650 PPD/Watt, which is very good.

Screen Shot from F@H V7 Client showing Estimated Points per Day:

1060 TI Client

Nvidia GTX 1060 Folding @ Home Results: Windows V7 Client

Here are the averaged results based on actual returned work units

(Graph courtesy of http://folding.extremeoverclocking.com/)

1060 GTX PPD History

NVidia 1060 GTX Folding PPD History

Note that in this plot, the reported results previous to the circled region are also from the 1060, but I didn’t have it running all the time.  The 305K PPD average is generated only from the work units returned within the time frame of the red circle (7/12 thru 7/21)

Production and Efficiency Plots

Nvidia 1060 PPD

NVidia GTX 1060 Folding@Home PPD Production Graph

Nvidia 1060 PPD per Watt

Nvidia GTX 1060 Folding@Home Efficiency Graph


For about $250 bucks (or $180 used if you get lucky on eBay), you can do some serious disease research by running Stanford University’s Folding@Home distributed computing project on the Nvidia GTX 1060 graphics card.  This card is a good middle ground in terms of price (it is the entry-level in NVidia’s current generation of GTX series of gaming cards).  Stepping up to a 1070 or 1080 will likely continue the trend of increased energy efficiency and performance, but these cards cost between $400 and $800.  The GTX 1060 reviewed here was still very impressive, and I’ll also point out that it runs my old video games at absolute max settings (Skyrim, Need for Speed Rivals).  Being a relatively small video card, it easily fits in a mid-tower ATX computer case, and only requires one supplemental PCI-Express power connector.  Doing over 300K PPD on only 185 watts, this Folding@home setup is both efficient and fast. For 2017, the NVidia 1060 is an excellent bang-for-the-buck Folding@home Graphics Card.

Request: Anyone want to loan me a 1070 or 1080 to test?  I’ll return it fully functional (I promise!)

F@H Efficiency: Overclock or Undervolt?

Efficiency Tweaking

After reading my last post about the AMD Phenom II X6 1100T’s performance and efficiency, you might be wondering if anything can be done to further improve this system’s energy efficiency.  The answer is yes, of course!  The 1100T is the top-end Phenom II processor, and is unlocked to allow tweaking to your heart’s content.  Normal people push these processors higher in frequency, which causes them to need more voltage and use more power.  While that is a valid tactic for gaining more raw points per day, I wondered if the extra points would be offset by a non-proportional increase in power consumption.  How is efficiency related to clock speed and voltage?  My aim here is to show you how you can improve your PPD/Watt by adjusting these settings.  By increasing the efficiency of your processor, you can reduce the guilt you feel about killing the planet with your cancer-fighting computer.  Note that the following method can be applied to any CPU/motherboard combo that allows you to adjust clock frequencies and voltages in the BIOS.  If you built your folding rig from scratch, you are in luck, because most custom PCs allow this sort of BIOS fun.  If you are using your dad’s stock Dell, you’re probably out of luck.

AMD Phenom II X6: Efficiency Improved through Undervolting

The baseline stats for the X6 Phenom 1100T are 3.3 GHz core speed with 2000 MHz HyperTransport and Northbridge clocks. This is achieved with the CPU operating at 1.375v, with a rated TDP (max power consumption) of 125 watts. Running the V7 Client in SMP-6 with my pass key, I saw roughly 12K ppd on A3 work units.  This is what was documented in my blog post from last time.

Now for the fun part.  Since this is a Black Edition processor from AMD, the voltages, base frequencies, and multipliers are all adjustable in the system BIOS (assuming your motherboard isn’t a piece of junk).  So, off I went to tweak the numbers.  I let the system “soak” at each setting in order to establish a consistent PPD baseline.  I got my PPD numbers by verifying what the client was reporting with the online statistics reporting.  Wattage numbers come from my trusty P3 Kill-A-Watt meter.

First, I tried overclocking the processor.  I upped the voltage as necessary to keep it stable (stable = folding overnight with no errors in F@H or my standard benchmark tests).  It was soon clear that from an efficiency standpoint, overclocking wasn’t really the way to go.  So, then I went the other way, and took a bit of clock speed and voltage out.

F@H Efficiency Curve: AMD Phenom II X6 1100T

F@H Efficiency Curve: AMD Phenom II X6 1100T

These results are very interesting.  Overclocking does indeed produce more points per day, but to go to higher frequencies required so much voltage that the power consumption went up even more, resulting in reduced efficiency.  However, a slight sacrifice of raw PPD performance allowed the 1100T to be stable at 1.225 volts, which caused a marked improvement in efficiency.  With a little more experimenting on the underclocking / undervolting side of things, I bet I could have got this CPU to almost 100 PPD / Watt!


PPD/Watt efficiency went up by about 30% for the Phenom II X6 1100T, just by tweaking some settings in the BIOS.  Optimizing core speed and voltage for efficiency should work for any CPU (or even graphics card, if your card has adjustable voltage).  If you care about the planet, try undervolting / underclocking your hardware slightly.  It will run cooler, quieter, and will likely last longer, in addition to doing more science for a given amount of electricity.

PPD/Watt Shootout: Uniprocessor Client is a Bad Idea

My Gaming / Folding computer with Q6600 / GTX 460 Installed

My Gaming / Folding computer with Q6600 / GTX 460 Installed

Since the dawn of Folding@Home, Stanford’s single-threaded CPU client known as “uniprocessor” has been the standard choice for stable folding@home installations.  For people who don’t want to tinker with many settings, and for people who don’t plan on running 24/7, this has been a good choice of clients because it allows a small science contribution to be done without very much hassle.  It’s a fairly invisible program that runs in the background and doesn’t spin up all your computer’s fans and heat up your room.  But, is it really efficient?  

The question, more specifically targeted for folding freaks reading this blog, is this:  Does the uniprocessor client make sense for an efficient 24/7 folding@home rig?  My answer:  a resounding NO!  Kill that process immediately!

A basic Google search on this will show that you can get vastly more points per day running the multicore client (SMP), a dedicated graphics card client (GPU), or both.  Just type “PPD Uniprocessor SMP Folding” into Google and read for about 20 minutes and you’ll get the idea.  I’m too lazy to point to any specific threads (no pun intended), but the various forum discussions reveal that the uniprocessor client is slower than slow.  This should not be surprising.  One CPU core is slower than two, which is slower than three!  Yay, math!

Also, Stanford’s point reward system isn’t linear but exponential.  If you return a work unit twice as fast, you get more than twice as many points as a reward, because prompt results are very valuable in the scientific world.  This bonus is known as the Quick Return Bonus, and it is available to users running with a passkey (a long auto-generated password that proves you are who you say you are to Stanford’s servers).  I won’t regurgitate all that info on passkeys and points here, because if you are reading this site then you most likely know it already.  If not, start by downloading Stanford’s latest all-in-one client known as Client V7.  Make sure you set yourself up with a username as well as a passkey, in case you didn’t have one.  Once you return 10 successful work units using your passkey, you can get the extra QRB points.  For the record, this is the setup I am using for this blog at the moment: V7 Client Version 7.3.6, running with passkey.

Unlike the older 6.x client interfaces, the new V7 client lets you pick the specific work package type you want to do within one program.  “Uniprocessor” is no longer a separate installation, but is selectable by adding a CPU slot within the V7 client and telling it how many threads to run.  V7 then downloads the correct work unit to munch on.

I thought I was talking efficiency!  Well, to that end, what we want to do is maximize the F@H output relative to the input.  We want to make as many Points per Day while drawing the fewest watts from the wall as possible.  It should be clear by now where this is going (I hope).  Because Stanford’s points system heavily favors the fast return of work units, it is often the case that the PPD/Watt increases as more and more CPU cores or GPU shaders are engaged, even though the resulting power draw of the computer increases.

Limiting ourselves to CPU-only folding for the moment, let’s have a look at what one of my Folding@Home rigs can do.  It’s Specs Time (Yay SPECS!). Here are the specs of my beloved gaming computer, known as Sagitta (outdated picture was up at the top).

  • Intel Q6600 Quad Core CPU @ 2.4 GHz
  • Gigabyte AMD Radeon HD 7870 Gigahertz Edition
  • 8 GB Kingston DDR2-800 Ram
  • Gigabyte 965-P S3 motherboard
  • Seasonic X-650 80+ Gold PSU
  • 2 x 500 GB Western Digital HDDs RAID-1
  • 2 x 120 MM Intake Fans
  • 1 x 120 MM Exhaust Fan
  • 1 x 80 MM Exhaust Fan
  • Arctic Cooling Freezer 7 CPU Cooler
  • Generic PCI Slot centrifugal exhaust fan
Ancient Pic of Sagitta (2006 Vintage).  I really need to take a new pic of the current configuration.

Ancient Pic of Sagitta (2006 Vintage). I really need to take a new pic of the current configuration.

You’ll probably say right away that this system, except for the graphics card, is pretty out of date for 2014, but for relative A to B comparisons within the V7 client this doesn’t matter.  For new I7 CPUs, the relative performance and efficiency differences seen by increasing the number of CPU cores for Folding reveals the same trend as will be shown here.  I’ll start by just looking at the 1-core option (uniprocessor) vs a dual-core F@H solve.

Uniprocessor Is Slow

As you can see, switching to a 2-CPU solve within the V7 client yields almost twice as many PPD (12.11 vs 6.82).  And, this isn’t even a fair comparison, because the dual-core work unit I received was one of the older A3 cores, which tend to produce less PPD than the A4 work units.

In conclusion, if everyone who is out there running the uniprocessor client switched to a dual-core client, FOLDING AT HOME WOULD BECOME TWICE AS EFFICIENT!  I can’t scream this loud enough.  Part of the reason for this is because it doesn’t take many more watts to feed another core in a computer that is already fired up and folding.  In the above example, we really started getting twice the amount of work done for only 13 more watts of power consumed.  THIS IS AWESOME, and it is just the beginning.  In the next article, I’ll look at the efficiency of 3 and 4 CPU Folding on the Q6600, as well as 6-CPU folding on my other computer, which is powered by a newer processor (AMD Phenom II X6 1100T). I’ll then move on to dual-CPU systems (non BIGADV at this point for those of you who know what this means, but we will get there too), and to graphics cards.  If you think 12 PPD/Watt is good, just wait until you read the next article!

Until next time…


Energy Efficient Power Supplies: Part 2

A Seasonic 80+ Gold Modular Power Supply is the Perfect PSU for my Dual Opteron 4184 12-Core Server

A Seasonic 80+ Gold Modular Power Supply is the Perfect PSU for my Dual Opteron 4184 12-Core Server

The last post gave an overview of why efficiency matters for power supplies. This post is focused on how to pull this off in practice.  The 80+ (80 Plus) certification is an optional certification that power supply makers can get on their retail PSUs by submitting samples for testing at an independent lab. There are various levels of efficiency rankings within the standard, but any unit that achieves the basic 80+ rating can be considered efficient compared to the average 60-70% efficient PSUs of old.

80+ Efficiency Table

80+ Efficiency Table

For around the clock computer operation, you should get the most efficient unit possible, although the 80+ Platinum and Titanium units can be cost prohibitive.  My recommendation is to stick with an 80+ Gold unit, because they are significantly more efficient than most power supplies and can be obtained without first having to sell a kidney on the black market.  Note that the greatest efficiency can theoretically be achieved by selecting a power supply that has a rated maximum wattage of twice what your computer requires to run F@H full-blast.  For example, if your shiny new F@H rig requires 300 watts of power to run, getting an 80+ Gold PSU rated at 600 watts should guarantee you an excellent efficiency rating of 90%.  This is because power supplies tend to be most efficient at 50% of their rated maximum load.

For many power supplies you can find an efficiency curve that graphs out the unit’s efficiency vs. load, but to save yourself valuable time you might as well just buy a reputable power supply from a good manufacturer that has the 80+ Gold certification.  As with any computer part, read the user reviews before purchase to avoid a serious frowney face later.  JonnyGuru.com has some excellent power supply reviews, and they test their review samples in a much more grueling temperature environment than the 80+ standard requires. When buying from Newegg, just filter your PSU search by efficiency rating and then by user reviews to immediately find some good candidates.  My personal favorite is the Seasonic X-series of Gold-rated PSUs, although Antec, PC Power & Cooling, Thermaltake, Cooler Master, Corsair, and many others also make good units.  I have been using the Seasonic X-650 Gold, which is a great power supply for a bunch of reasons other than efficiency (modular cables, multiple PCI Express power connections, a smart fan, the latest ATX standard, great build quality, and so on until I’m blue in the face).  The Seasonic has reduced my desktop’s power consumption by over 32 watts at idle and 49 watts at load, compared to the Ultra X2 connect 500 watt PSU I had before.  I pitched the old one into the computer recycling bin at the local transfer station to make sure it stays out of service.  It made a nice sounding kerthunk, by the way.  (Random environmental tip: Most city dumps take recycle computer electronics for free, so take your old wasteful power supply as well as any of those nasty compact fluorescent mercury-ridden light bulbs to the dump for recycling instead of throwing them in the trash.)

Efficient Power Supplies: Part 1

Good morning!  This is an intro article…feel free to skip if you already know what efficiency means for power supplies.  Part 2 goes into detail of the 80 Plus standard and is likely a more enthralling read for you spec heads!

Let’s talk about the most important piece of hardware that a desktop computer can have…the power supply!  This little guy is responsible for electrifying all the goodies inside your computer.  Furthermore, a good power supply protects your computer from dirty power (voltage spikes, EMI ripple, power fluctuations, etc).  If you have ever read an article on custom desktop building, you probably know how crucial a good power supply is, as well as the consequences of using a cheap PSU.  Suffice it to say that, for the sake of your computer’s health, this is one area where you don’t want to skimp on cost.

There is one trait of quality power supplies that is often overlooked, and that is energy efficiency.  In a perfect world, a PSU would convert every watt of 120 V AC input power into usable DC power.  In reality a portion of the power is lost as heat.  The more efficient a power supply, the less energy it wastes as heat.  In other words, your computer simply draws fewer watts from the wall.

Having an efficient power supply is crucial for F@H contributors and non-folders alike, because it will make your computer less power hungry no matter what it is doing.  From gaming and graphics design to office work and Folding@Home, an efficient PSU will put a smile on your P3’s cute little face.  (If you don’t get the reference, please also read the previous post about Watt meters)

Before I go on, I should note that the target audience of this article is those who have built or are building their own custom desktop.  People with laptops or with name-brand consumer desktops are sometimes out of luck because the power supplies are often proprietary and can’t be upgraded.  However, it doesn’t hurt to find out from the manufacturer of your computer what the efficiency of your power supply is.  Some brands, such as Dell, HP, and Apple (among others) do have energy efficient power supplies of varying levels in their machines.

Cheap No-Name Brand Power Supply Unit that Came with a Case Bundle

Cheap No-Name Brand Power Supply Unit

If your power supply looks as lame as the one in the above pic, then it probably has an efficiency rating of 60 to 70 percent.  This means that if your computer parts need roughly 200 watts of power to run, your PSU might draw 250 watts or more from the wall in order to supply the 200 watts of DC power.  That extra 50+ watts is wasted as heat.

PC Power & Cooling SILENCER PSU

PC Power & Cooling SILENCER PSU

Seasonic SS-380GB PSU Installed

But, if your power supply looks like the one in Pic # 2 or #3, it might be closer to 80 or 90 percent efficient.  For that same 200 watt load, it is only drawing perhaps 220 watts from the wall.  The thirty watt difference might not seem like much, but for a Folding rig running 24/7 the wasted wattage of the el-cheapo unit adds up.  Let’s assume we are running a machine with the craptastic PSU.  To calculate the total extra energy wasted relative to the better PSU (remember, watts is a power quantity, which means energy/time), we need to multiply the wasted wattage by the amount of time the computer was in service to get an energy quantity in watt-hours.  So, 30 watts * 24 hours/day * 365 days/year = 262800 watt-hours.  Converting to kilowatt hours (dividing by 1000) gives 262.8 kWh.  Assuming an average electricity cost of ten cents per kWh, we get an annual cost of 262.8 * 0.10 $/kWh = $26.28.  Assuming the folding computer is running with that same power supply for 5 years (mine has been going for longer), that is over $125 wasted dollars, not to mention a slap in the face for poor planet Earth!  A good energy efficient PSU could have been bought for $40 in the first place to negate this wasted energy cost and lessen the environmental impact.

So how can you spot an efficient power supply unit?  Well, for that you can go by the independent test & certification program known as 80+.  I will cover this in detail in the next article, so that people who want to jump right into the specs and skip this intro can do so.

Efficiency Defined

Give Me Efficiency or Give Me an Empty CPU Socket!

You could always just remove your CPU to slash your power consumption, but no cancer gets cured that way.

Hi guys & gals!

Before I start talking the specifics of various computer hardware configurations, let’s get the definition of efficiency out of the way.  After all, computational efficiency is where it’s at!  That is the whole point of this blog.

Warning: Math Time (feel free to skip down a few paragraphs if you know this already):

Efficiency is a numerical ratio of two work or power quantities.  It has the general form of OUTPUT / INPUT.  Basically, it tells you how much desired work you got out of some process for a certain amount of input.  For a true mechanical or electrical efficiency, the units of both the numerator and denominator would be the same.  For example, our microwave at work generates 1200 watts of cooking power inside the machine, but draws 1488 watts at the wall.  Thus, it’s efficiency in terms of cooking power is: 1200 / 1488 = .806.  Multiply this fraction by 100 to get the efficiency percentage, and you see that our microwave is 80.6 % efficient at heating food.  Where did the rest of the energy go?  Well, in this case there was the power required to run the computerized guts, spin the turn table, spin the fan, light the light, etc.  There are also electrical losses in the circuits that get dissipated as heat into the microwave’s chassis.

Another good example is light bulbs.  In this case, we are looking at something called efficacy, not an electrical efficiency (but it is directly related), because the units in the numerator and denominator are going to be different.  It is possible, but less intuitive, to convert into a true efficiency ratio (visual power out / electrical power in), but I’m not going to go there because it hurts my brain.  Anyway, the good old 60 watt light bulb uses 60 watts (gosh) to create about 800 lumens of light.  By comparison, compact fluorescent bulbs use about 12-14 watts, and the new CREE LED bulbs use 9.5 watts.  Thus, the luminous efficacy of a 60 watt light bulb is 800 lm / 60 w = 13.3 lumens per watt.  On the other hand, the luminous efficacy of the awesome CREE LED bulbs (I have them everywhere in my house now) is 800 lm / 9.5 w = 84 lm/watt.  That is over 6 times more efficient than the old-fashioned tungsten filament bulb!  (Aside: you really should change out any 60 watt or 100 watt bulbs you still have in your house with CFL or CREE LED bulbs.  This is a great step towards negating your F@H carbon footprint! PLUS, IT  SAVES YOU MONEY!)

So, how does this relate to folding?  While, with F@H there is an accepted definition of work done, called Points.  The more work units complete, the more points you get.  Also, the faster your computer does the work units the more points you get (big time…it is exponential.  More on Stanford’s Points scheme later…).  So, to make this a power quantity (work done over time), we need to divide the # of points your computer is generating by the number of days it took to get those points.  Thus, we get to the most common rating of Folding@Home performance: The Points per Day unit (PPD).

We can obtain a rough “efficiency” of a F@H computer by dividing the PPD (scientific work output) by the electrical power (input) of the computer.  Note that this is really more of an efficacy rating (how effective something is at producing a desired output) but everyone on the interwebs calls it an efficiency so I will suppress the engineer in me and go with the flow of electrons on this one.

So, our F@H efficiency is PPD/Watt.  This is so central to this blog that I am going to say it again, for those skimmers who don’t like reading.

F@H efficiency is measured in Points Per Day / Watt!!!!

This is what we are concerned with.  Slow computers from 5 years ago still use a similar amount of electricity as today’s modern ones, but they are bricks when it comes to processing.  The amount of slow, crappy computers that are still running F@H is insane, and it is growing!  This is one of the main reasons why Folding gets a bad rap…the overall efficiency of the supercomputer as a whole is terrible.  We need to fix this!  Thankfully, Stanford & Sony have already ditched F@H on the Playstation 3.  This partnership was once one of the greatest boons to the F@H network, as back in the day the PS3’s were some of the fastest machines on the planet.  But, as computers got faster and the years went by, PS3’s became a poor choice relative to the new, super-efficient desktop processors and graphics cards.  Thus, F@H was removed as an option for Playstation users (much to their annoyance).  However, there is less management going on with the computer side of the F@H network (which is currently all of it).  If I want to, I can pull out my old Pentium 4 machine and get 100 PPD / 150 watts of power = 0.67 PPD/Watt!  But why would I want to spend money & kill the planet for that measly amount of performance?

I get the sense that you are likely getting the point by now, and thus I probably can stop rambling.  I can talk efficiency and specs all day (much to my wife’s annoyance).  The key takeaway is this:  Computers are always getting faster and more efficient.  F@H is as well, but is hindered by the amount of old computers that are stuck in yesteryear’s levels of efficiency.  We need to fix this.  We want to make our electrical contribution worth something.  WE WANT TO GENERATE AS MANY PPD/WATT AS POSSIBLE!  And that is exactly what we are going to do.  Over the next few posts, we’re going to talk in slightly less general terms about two things: how to Maximize PPD and how to Minimize Computer Power Consumption.  The latter is especially relevant to any computing project, even gaming or home computer use, so please feel free to read on even if you don’t plan to fold yourself.  Saving the planet and saving money by not using any more electricity than you need to accomplish a task is a worthy goal.  Tune in next time for the first hardware article: PC Power Supplies!