Category: Future of performance evaluation

WebXPRT in 2017

on December 8, 2016

Over the last few weeks, we’ve discussed the future of HDXPRT and BatteryXPRT. This week, we’re discussing what’s in store for WebXPRT in 2017.

WebXPRT is our most popular tool. Manufacturers, developers, consumers, and media outlets in more than 350 cities and 57 countries have run WebXPRT over 113,000 times to date. The benchmark runs quickly and simply in most browsers and produces easy-to-understand results that are useful for comparing web browsing performance across a wide variety of devices and browsers. People love the fact that WebXPRT runs on almost any platform that has a web browser, from PCs to phones to game consoles.

More people are using WebXPRT in more places and in more ways than ever before. It’s an unquestioned success, but we think this is a good time to make it even better by beginning work on WebXPRT 2017. Any time change comes to a popular product, there’s a risk that faithful fans will lose the features and functionality they’ve grown to love. Relevant workloads, ease of use, and extensive compatibility have always been the core components of WebXPRT’s success, so we want to reassure users that we’re committed to maintaining all of those in future versions.

Some steps in the WebXPRT 2017 process are straightforward, such as the need to reassess the existing workload lineup and update content to reflect advances in commonly used technologies. Other steps, such as introducing new workloads to test emerging browser technologies, may be tricky to implement, but could offer tremendous value in the months and years ahead.

Are there test scenarios or browser technologies you would like to see in WebXPRT 2017, or tests you think we should get rid of? Please let us know. We want to hear from you and make sure that we’re crafting a performance tool that continues to meet your needs.

Bill

Posted in BatteryXPRT 2014 for Android, Future of performance evaluation, HDXPRT, HTML5, Performance benchmarking, Web-based testing, WebXPRT, WebXPRT 2017 |

Machine learning

By Bill Catchings

on November 23, 2016

A couple months ago I wrote about doing an inventory of our XPRT tools. Part of that is taking a close look at the six existing XPRTs. The first result of that effort was what I recently wrote about HDXPRT. We’re also looking at emerging technology areas where the BenchmarkXPRT Community has expertise that can guide us.

One of the most exciting of these areas is machine learning. It has rapidly gone from interesting theoretical research (they called them “neural nets” back when I was getting my computer science degree) to something we all use whether we realize it or not. Machine learning (or deep learning) is in everything from intelligent home assistants to autonomous automobiles to industrial device monitoring to personalized shopping in retail environments.

The challenge with developing a benchmark for machine learning is that these are still the early days of the technology. In the past, XPRTs have targeted technologies later in the product cycle. We’re wondering how the XPRT model and the members of its community can play a role here.

One possible use of a machine-learning XPRT is with drones, a market that includes many vendors. Consumers, hobbyists, builders, and the companies creating off-the-shelf models could all benefit from tools and techniques that fairly compare drone performance.

The best approach we’ve come up with to define a machine-learning XPRT starts with identifying common areas such as computer vision, natural language processing, and data analytics, and then, within each of those areas, identifying common algorithms such as AlexNet, GoogLeNet, and VGG. We would also look at the commonly used frameworks such as Caffe, Theano, TensorFlow, and CNTK.

The result might differ from an existing XPRT where you simply run a tool and get a result. Instead, it might take the form of sample code and workloads. Or, maybe even one or two executables that could be used in the most common environments.

At this point, our biggest question is, What do you think? Is this an area you’re interested in? If so, what would you like to see a machine-learning XPRT do?

We’re actively engaging with people in these emerging markets to gauge their interest as well. Regardless of the feedback, we’re excited about the possibilities!

Bill

Posted in Collaborative benchmark development, Drones, Future of performance evaluation, HDXPRT, Machine learning |

HDXPRT’s future

By Bill Catchings

on November 3, 2016

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

Posted in Application-based benchmarks, BenchmarkXPRT development community, Collaborative benchmark development, Future of performance evaluation, HDXPRT, HDXPRT development process, Performance benchmarking, What makes a good benchmark?, Windows 10 |

Rebalancing our portfolio

By Bill Catchings

on September 29, 2016

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

Posted in Android, Application-based benchmarks, BenchmarkXPRT development community, Chrome OS, Collaborative benchmark development, CrXPRT, Future of performance evaluation, HDXPRT, WebXPRT, What makes a good benchmark? |

Doing things a little differently

By Eric Hale

on September 8, 2016

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

Posted in Apple, Benchmark metrics, Benchmarking, Future of performance evaluation, Machine learning, Phones, What makes a good benchmark? |

A Chrome-plated example

By Eric Hale

on September 1, 2016

A couple of weeks ago, we talked about how benchmarks have to evolve to keep up with the changing ways people use their devices. One area where we are expecting a lot of change in the next few months is Chromebooks.

These web-based devices have become very popular, even outselling Macs for the first time in Q1 of this year. Chromebooks run Google Apps and a variety of third-party Chrome apps that also run on Windows, Mac, and Linux systems.

Back in May, Google announced that Android apps would be coming to Chromebooks. This exciting development will bring a lot more applications to the platform. Now, Google has announced that they will be “moving away” from the Chrome apps platform and will be phasing out Chrome app support on other platforms within the next two years.

Clearly, the uses of Chromebooks are likely to change a lot in coming months. Interestingly, part of the rationale Google gives for this decision is the development of powerful new Web APIs, which will have implications for WebXPRT as well.

As we’ve said before, we’ll be watching and adapting as the applications change.

Eric

Posted in Application-based benchmarks, Benchmarking, Chrome OS, Future of performance evaluation, Google, WebXPRT |

Category: Future of performance evaluation

WebXPRT in 2017

Machine learning

HDXPRT’s future

Rebalancing our portfolio

Doing things a little differently

A Chrome-plated example

Check out the other XPRTs: