Sun use DCiE (1/PUE) in its Eco Services Offering

Looking up what companies are leveraging PUE or DCiE, I found this marketing document on Sun's website, Accurately Measuring Datacenter Power Efficiency.

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You can tell this was written by a marketing team as there is no mention of DCiE or PUE, even though it shows this formula.

 

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I ran a search on IBM's website and I can't find any mention of PUE except in a powerpoint presentation by Eaton.

Maybe Sun can help Google measure its data centers below 5MW.

Google says they eliminated data for facilities below 5MW.

Such a strong claim demands evidence, especially in light of recent criticism of companies "gaming the numbers." On this page we will explain our measurements in detail to ensure that they are realistic and accurate. It is worth noting that we only show data for facilities with an actual IT load above 5MW, to eliminate any inaccuracies that can occur when measuring small values. This section is aimed at data center experts, but we have tried to make it accessible to a general technical audience as well.

If we believe Google's claim that you can't measure accurately below 5MW (google's definition of a small value), then the majority of data centers have an excuse for not publishing their numbers as they can't be accurate according to Google PR/Marketing.

What is the true reason why Google excludes data centers below 5MW?

  • Too expensive to instrument.
  • Google doesn't have any data centers it built below 5MW.
  • The PUE of these data centers is high.
  • Google doesn't have good data on the data centers below 5MW.
  • There are a lot of less than 5MW data centers, and it was easier to talk about a few big energy efficient data centers.
  • Instrumentation is inaccurate at less than 5MW.
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Six Products, Six Carbon Footprints, Transportation Less than 1% of footprint

WSJ has an informative article on the carbon footprint of six products.

[The Journal Report: Environment]

First came organic. Then came fair trade. Now makers of everything from milk to jackets to cars are starting to tally up the carbon footprints of their products. That's the amount of carbon dioxide and other greenhouse gases that get coughed into the air when the goods are made, shipped and stored, and then used by consumers.

In the Gelsi household, reducing their carbon footprint is a family affair -- they even wrote a musical about it. MarketWatch reporter Steve Gelsi offers tips for saving the environment and saving money while doing so.

So far, these efforts raise as many questions as they answer. Different companies are counting their products' carbon footprints differently, making it all but impossible for shoppers to compare goods. And even if consumers come to understand the numbers, they might not like what they find out.

For instance, many products' global-warming impact depends less on how they're made than on how they're used. That means the easiest way to cut carbon emissions may be to buy less of a product or use it in a way that's less convenient

Patagonia had a dose of reality calculating transportation was 1% of the carbon footprint.

Patagonia Inc.'s Talus jacket looks like a naturalist's dream. In fact, its carbon footprint is 66 pounds. That, Patagonia notes on its Web site, is 48 times the weight of the jacket itself.

Over the past year, the Ventura, Calif., outdoor-equipment maker has computed and posted on its Web site the carbon footprints of 15 of its products. Because most of Patagonia's products are made in Asia or Latin America and sold in the U.S., the company expected that a big chunk of the carbon footprints came from transportation. It was wrong.

The fabric for the Talus is made in China, the zippers come from Japan, and the jacket is sewn in Vietnam. Yet all that transportation adds up to less than 1% of the product's total carbon footprint, Patagonia says. The majority of the footprint -- 71%, or about 47 pounds -- comes in producing the polyester, which originates with oil.

"If we had listened to the rhetoric out there at the time, which was all around miles, we could have spent years rearranging our supply chain to reduce transportation, when really that's not the bulk of our concern," says Jill Dumain, Patagonia's director for environmental analysis. "There's a lot of reasons to have a tight supply chain, but environmentalism isn't one of them."

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HP’s PUE article, quotes HP Employee Chris Malone, Ahh Chris works for Google Now

Found this article on HP’s Enterprise Magazine, discussing PUE for data center efficiency. At the time it was written, Chris Malone was an HP employee, but now he works for Google.  Transforming Your Enterprise Magazine

Winter 2008


Metrics drive efficiency in the data center

In an effort to understand where data center energy inefficiencies lie, companies are adopting standardized metrics of PUE and CPE to determine the initiatives required for optimization.

Metrics drive efficiency in the data centerEnergy consumption and inefficiency within data centers is a well publicized problem and a key concern for IT organizations. Gartner has predicted that, "By 2011, more than 70 percent of U.S. enterprise data centers will face tangible disruptions related to floor space, energy consumption and/or costs."*

Before data center inefficiency can be resolved, experts say it must be characterized and tracked in a consistent manner.

“Our investigations have shown that most data centers are inefficient, expending more power for cooling than for running the IT equipment,” notes Dr. Chris Malone, Thermal Technologies Architect for HP. “Until recently, there was no established method for benchmarking data center energy consumption, making it extremely difficult to characterize the full extent of the problem.”

Malone suggests a standardized evaluation of and rating for data center energy consumption to help companies determine:

  • How well is a data center running relative to others in the industry?
  • Are new data centers more efficient than the old ones?
  • Which data centers should be retired?
  • Do best practices really improve efficiency?
  • Do new technologies actually perform as suppliers promise?

HP didn’t quote Christian Belady who was a PUE innovator at HP. 

For those of you who didn’t know Christian is now at Microsoft. Chris is at Google.  Too bad HP couldn’t keep these guys at HP. Otherwise, we would be discussing HP’s innovations in data center efficiency.

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Compare Sun’s PUE/Data Center Disclosure vs. Google’s

Sun’s PR team sent me some blog entries on their PUE efforts.

One is Sun discussing their achieving a 1.28 PUE.

I'll show you mine...


So how efficient is your datacenter?

Last month I received some pretty cool news.  The Chill-Off we have been hosting for the Silicon Valley Leadership Group (SVLG) in their datacenter demonstration project, was completed.  This was a head to head test against APC In-Row, Liebert XDV, Spraycool, Rittal Liquid Racks and IBM Rear Door Heat Exchanger. Sun was the host that provided the datacenter, plant, compute equipment, and support.  Lawrence Berkeley National Labs (LBNL) was the group conducting the test on behalf of the California Energy Commission (CEC)  The results from this test will be published in a report in June of this year and we will be hosting the event.

But one piece of information came out of this that I could not wait to share.  As part of the chill-off, LBNL did a baseline of our plant in Santa Clara.  Mike Ryan on my staff then captured the usage data for the remaining portions of the datacenter.  This gave us our PUE or DCiE (pick you favorite) number.

Surprise, Surprise!

I knew that our datacenter would be efficient because of the way we had designed it, but I did not have any data to back it up yet.  We had been telling our customers, and others that toured the center, that we are pretty sure we would be under the industry targeted PUE of 2 (Created by Christian Belady from the Green Grid).  That was a conservative number.  But when I got the data back, even I was surprised at how efficient it was.

We achieved a PUE of 1.28!

Google says they eliminated data for facilities below 5MW.

Such a strong claim demands evidence, especially in light of recent criticism of companies "gaming the numbers." On this page we will explain our measurements in detail to ensure that they are realistic and accurate. It is worth noting that we only show data for facilities with an actual IT load above 5MW, to eliminate any inaccuracies that can occur when measuring small values. This section is aimed at data center experts, but we have tried to make it accessible to a general technical audience as well.

But given Google’s claim of measurement accuracy, it would seem like they should be able to measure numbers below 1MW like Sun has.

Error Analysis

To ensure our PUE calculations are accurate, we performed an uncertainty analysis using the root sum of the squares (RSS) method.  Our uncertainty analysis shows that the overall uncertainty in the PUE calculations is less than 2% (99.7% confidence interval).  Our power meters are highly accurate (ANSI C12.20 0.2 compliant) so that measurement errors have a negligible impact on overall PUE uncertainty.  The contribution to the overall uncertainty for each term described above is outlined in the table below.

Here are more technical details on Sun’s PUE calculations.

Sun exposes more details than Google as they want your business.

Better yet, would you like Sun to help design your datacenter to achieve the same efficiencies?  Let us drive the next generations physical and technical solutions for you.  Sun's Eco Virtualization practice can do just that.  Email me at dean.nelson@sun.com and I'll tell you how.

What is Google’s motivation for its PUE disclosure?

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James Hamilton Analyzes Google’s Data Center ideas – Water and PUE

James Hamilton analyzes Google’s Data Center publication.

A Small Window into Google's Data Centers

Google has long enjoyed a reputation for running efficient data centers. I suspect this reputation is largely deserved but, since it has been completely shrouded in secrecy, that’s largely been a guess built upon respect for the folks working on the infrastructure team rather than anything that’s been published. However, some of the shroud of secrecy was lifted last week and a few interesting tidbits were released in Google Commitment to Sustainable Computing.

On server design (Efficient Servers), the paper documents the use of high-efficiency power supplies and voltage regulators, and the removal of components not relevant in a service-targeted server design. A key point is the use of efficient, variable-speed fans. I’ve seen servers that spend as much as 60W driving the fans alone. Using high efficiency fans running at the minimum speed necessary based upon current heat load can bring big savings. An even better approach is employed by Rackable Systems in their ICE Cube Modular Data Center design (First Containerized Data Center Announcement) where they eliminate server fans entirely.

Parts I liked about James efforts are #1 – he discusses water.

It’s good to see water conservation brought up beside energy efficiency. It’s the next big problem for our industry and the consumption rates are prodigious. To achieve efficiency, most centers have cooling towers which allow them to avoid the use of energy-intensive direct-expansion chillers except under unusually hot and humid conditions. This is great news from an energy efficiency perspective, but cooling towers consume water in two significant ways. The first are evaporative losses which are hard to avoid in wet tower designs (other less water-intensive designs exist). The second is caused by the first. As water evaporates from the closed system, the concentrations of dissolved solids and other contaminants present in the supply water left behind by evaporation continue to rise. These high concentrations are dumped from the system to protect it and this dumping is referred to as blow-down water. Between make-up and blow-down water, a medium-sized, 10MW facility, built to current industry conventions, can go through ¼ to ½ million gallons of water a day.

The paper describes a plan to address this problem in the future by moving to recycled water sources. This is good to see but I argue the industry needs to reduce overall water consumption, whether the source is fresh or recycled. The combination of higher data center temperatures and aggressive use of air-side economization are both good steps in that direction and industry-wide we’re all working hard on new techniques and approaches to reduce water consumption.

Then #2 PUE.

The section on PUE is the most interesting in that the are documenting an at-scale facility running at a PUE of 1.13 during a quarter. Generally, you want full-year numbers since these numbers are very load and weather dependent. The best annual number quoted in the paper is 1.15 which is excellent. That means that for every watt delivered to servers 0.15W is lost in power distribution and cooling.

This number, with pure air-side cooling and good overall center design, is quite attainable. But, elsewhere in the document, they described the use of cooling towers. Attaining a PUE of 1.15 with a conventional water-based cooling system is considerably more difficult. On the power distribution side, conventional designs waste about 8% to 9% of the power delivered. A rough breakdown of where it goes is 3 transformers taking 115KV down to 13.2KV down to 480KV and then down to 208KV for delivery to the load. Good transformer designs run around 99.7% efficiency. The uninterruptable power supply can be as poor as 94%, and roughly 1% is lost in switching and conductors. That approach gets us to 8% lost in distribution. We can easily eliminate one layer of transformers and either use a high efficiency bypass UPS. Let’s use 97% efficiency for the UPS. Those two changes will get us 4% to 5% lost in distribution. Let’s assume we can reliably hit 5% power distribution losses. That leaves us with 10% for all the losses to the mechanical systems. Powering the Computer Room Air Handlers, the water pumps etc. at only 10% overhead would be both difficult and more impressive.

The 1.15 PUE with pure air-side economization in the right climate looks quite reasonable, but powering a conventional, high-scale, air and water, multi-conversion cooling system at this efficiency looks considerably harder to me. Unfortunately, there is no data published in the paper on the approach and whether it was simply attained by relying on favorable weather conditions and air-side economization with the water loops idle.

And last, #3

The paper concludes that “if all data centers operated at the same efficiency as ours, the U.S. alone would save enough electricity to power every household within the city limits of Atlanta, Los Angeles, Chicago, and Washington, D.C.”. This is hard to independently verify without much more information than offered by the paper. Most of the techniques employed are not discussed in the paper published last week. If the large service providers like Google, Microsoft, Yahoo, Beidu, Amazon and a handful of others don’t publish the details, the rest of the world’s data centers will never run as efficiently as described in the paper. Only high-scale datacenter users can afford the R&D program to spend on increased efficiency and water consumption elimination. I’m arguing it’s up to all of us working in the industry to publish the details to allow smaller-scale deployments to operate at similar efficiency levels. If we don’t, it’ll continue to be the case that US data centers alone will be needlessly spending enough power to support every household in Atlanta, Los Angeles, Chicago, and Washington DC. Each day, every day.

Hopefully other press and bloggers will read James’s post, and provide other points beyond Google’s marketing efforts.

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