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Category: What makes a good benchmark?

Experience is the best teacher

One of the core principles that guides the design of the XPRT tools is they should reflect the way real-world users use their devices. The XPRTs try to use applications and workloads that reflect what users do and the way that real applications function. How did we learn how important this is? The hard way—by making mistakes! Here’s one example.

In the 1990s, I was Director of Testing for the Ziff-Davis Benchmark Operation (ZDBOp). The benchmarks ZDBOp created for its technical magazines became the industry standards, because of both their quality and Ziff-Davis’ leadership in the technical trade press.

WebBench, one of the benchmarks ZDBOp developed, measured the performance of early web servers. We worked hard to create a tool that used physical clients and tested web server performance over an actual network. However, we didn’t pay enough attention to how clients actually interacted with the servers. In the first version of WebBench, the clients opened connections to the server, did a small amount of work, closed the connections, and then opened new ones.

When we met with vendors after the release of WebBench, they begged us to change the model. At that time, browsers opened relatively long-lived connections and did lots of work before closing them. Our model was almost the opposite of that. It put vendors in the position of having to choose between coding to give their users good performance and coding to get good WebBench results.

Of course, we were horrified by this, and worked hard to make the next version of the benchmark reflect more closely the way real browsers interacted with web servers. Subsequent versions of WebBench were much better received.

This is one of the roots from which the XPRT philosophy grew. We have tried to learn and grow from the mistakes we’ve made. We’d love to hear about any of your experiences with performance tools so we can all learn together.

Eric

Creating a machine-learning benchmark

Recently, we wrote about one of the most exciting emerging technology areas, machine learning, and the question of what role the XPRTs could play in the field.

Experts expect machine learning to be the analytics backbone of the IoT data explosion. It is a disruptive technology with potential to influence a broad range of industries. Consumer and industrial applications that take advantage of machine-learning advancements in computer vision, natural language processing, and data analytics are already available and many more are on the way.

Currently, there is no comprehensive machine-learning or deep-learning benchmark that includes home, automotive, industrial, and retail use cases. The challenge with developing a benchmark for machine learning is that these are still the early days of the technology. A fragmented software and hardware landscape and lack of standardized implementations makes benchmarking machine learning complex and challenging.

Based on the conversations we’ve had over the last few weeks, we’ve decided to take on that challenge. With the community’s help, of course!

As we outlined in a blog entry last month, we will work with interested folks in the community, key vendors, and academia to pull together what we are internally calling MLXPRT.

While the result may differ substantially from the existing XPRTs, we think the need for something is great. Whether that will turn out to be a packaged tool or just sample code and workloads remains to be seen.

What we need most your help. We need both general input about what you would like to see as well as any expertise you may have. Let us know any questions you may have or ways you can help.

On a related note, I’ll be at CES 2017 in Las Vegas during the first week of January. I’d love to meet and talk more about machine learning, benchmarking, or the XPRTs. If you’re planning to be there and would like to connect, let us know.

We will not have a blog entry next week over the holidays, so we wish all of you a wonderful time with your families and a great start to the new year.

Bill

HDXPRT’s future

While industry pundits have written many words about the death of the PC, Windows PCs are going through a renaissance. No longer do you just choose between a desktop or a laptop in beige or black. There has been an explosion of choices.

Whether you want a super-thin notebook, a tablet, or a two-in-one device, the market has something to offer. Desktop systems can be small devices on your desk, all-in-ones with the PC built into the monitor, or old-style boxes that sit on the floor. You can go with something inexpensive that will be sufficient for many tasks or invest in a super-powerful PC capable of driving today’s latest VR devices. Or you can get a new Microsoft Surface Studio, an example of the new types of devices entering the PC scene.

The current proliferation of PC choices means that tools that help buyers understand the performance differences between systems are more important than they have been in years. Because HDXPRT is one such tool, we expect demand for it to increase.

We have many tasks ahead of us as we prepare for this increased demand. The first is to release a version of HDXPRT 2014 that doesn’t require a patch. We are working on that and should have something ready later this month.

For the other tasks, we need your input. We believe we need to update HDXPRT to reflect the world of high-definition content. It’s tempting to simply change the name to UHDXPRT, but this was our first XPRT and I’m partial to the original name. How about you?

As far as tests, what should a 2017 version of HDXPRT include? We think 4K-related workloads are a must, but aren’t sure whether 4K playback tests are the way to go. What do you think? We need to update other content, such as photo and video resolutions, and replace outdated applications with current versions. Would a VR test would be worthwhile?

Please share your thoughts with us over the coming weeks as we put together a plan for the next version of HDXPRT!

Bill

An exciting milestone for WebXPRT!

If you’re familiar with the run counter on WebXPRT.com, you may have noticed that WebXPRT recently passed a pretty significant milestone. Since we released WebXPRT 2013, users running WebXPRT 2013 and 2015 have successfully completed over 100,000 runs!

We’re thrilled about WebXPRT’s ongoing popularity, and we think that it’s due to the benchmark’s unique combination of characteristics: it’s easy to run, it runs quickly and on a wide variety of platforms, and it evaluates device performance using real-world tasks. Manufacturers, developers, consumers, and media outlets in more than 358 cities, from Aberdeen to Zevenaar, and 57 countries, from Argentina to Vietnam, have used WebXPRT’s easy-to-understand results to compare how well devices handle everyday tasks. WebXPRT has definitely earned its reputation as a “go-to” benchmark.

If you haven’t run WebXPRT yet, give it a try. The test is free and runs in almost any browser.

We’re grateful for everyone who’s helped us reach this milestone. Here’s to another 100,000 runs!

Justin

Rebalancing our portfolio

We’ve written recently about the many new ways people are using their devices, the growing breadth of types of devices, and how application environments also are changing. We’ve been thinking a lot about the ways benchmarks need to adapt and what new tests we should be developing.

As part of this process, we’re reviewing the XPRT portfolio. An example we wrote about recently was Google’s statement that they are bringing Android apps to Chrome OS and moving away from Chrome apps. Assuming the plan comes to fruition, it has big implications for CrXPRT, and possibly for WebXPRT as well. Another example is that once upon a time, HDXPRT included video playback tests. The increasing importance of 4K video might mean we should bring them back.

As always, we’re interested in your thoughts. Which tests do you see as the most useful going forward? Which ones do you think might be past their prime? What new areas do you like to see us start to address? Let us know!

Over the coming weeks, we’ll share our conclusions based on these market forces and your feedback. We’re excited about the possibilities and hope you are as well.

Bill

Doing things a little differently

I enjoyed watching the Apple Event live yesterday. There were some very impressive announcements. (And a few which were not so impressive – the Breathe app would get on my nerves really fast!)

One thing that I was very impressed by was the ability of the iPhone 7 Plus camera to create depth-of-field effects. Some of the photos demonstrated how the phone used machine learning to identify people in the shot and keep them in focus while blurring the background, creating a shallow depth of field. This causes the subjects in a photo to really stand out. The way we take photos is not the only thing that’s changing. There was a mention of machine learning being part of Apple’s QuickType keyboard, to help with “contextual prediction.”

This is only one product announcement, but it’s a reminder that we need to be constantly examining every part of the XPRTs. Recently, we talked a bit about how people will be using their devices in new ways in the coming months, and we need to be developing tests for these new applications. However, we must also stay focused on keeping existing tests fresh.  People will keep taking photos, but today’s photo editing tests may not be relevant a year or two from now.

Were there any announcements yesterday that got you excited? Let us know!

Eric

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