Tag Archives: benchmark

Out with the old, and in with the new

on February 14, 2019

What we now know as the BenchmarkXPRT Development Community started many years ago as the HDXPRT Development Community forum. At the time, the community was much smaller, and HDXPRT was our only benchmark. When a member wanted to run the benchmark, they submitted a request, and then received an installation DVD in the mail.

With hundreds of members, more than a half dozen active benchmarks, and the online availability of all our tools, the current community is a much different organization. Instead of the original forum, most of our interaction with members takes place through the blog, the monthly newsletter, direct email, and our social media accounts. Because of the way the community has changed, and because the original forum is no longer very active, we believe that the time and resources that we devote to maintaining the forum could be better spent on building and maintaining other community assets. To that end, we’ve decided to end support for the original BenchmarkXPRT forum.

As always, community members’ voices are an important consideration in what we do. If you have any questions or concerns about the decision to close down the original forum, please let us know as soon as possible.

On another note, we want to thank the community members who’ve participated in the HDXPRT 4 Community Preview. Testing has gone well, and we’re planning to release HDXPRT 4 to the public towards the end of next week!

Justin

XPRTs in the datacenter

By Bill Catchings

on September 6, 2018

The XPRTs have been very successful on desktops, notebooks, tablets, and phones. People have run WebXPRT over 295,000 times. It and other benchmarks such as MobileXPRT, HDXPRT, and CrXPRT are important tools globally for evaluating device performance on various consumer and business client platforms.

We’ve begun branching out with tests for edge devices with AIXPRT, our new artificial intelligence benchmark. While typical consumers won’t be able to run AIXPRT on their devices initially, we feel that it is important for the XPRTs to play an active role in a critical emerging market. (We’ll have some updates on the AIXPRT front in the next few weeks.)

Recently, both community members and others have asked about the possibility of the XPRTs moving into the datacenter. Folks face challenges in evaluating the performance and suitability to task of such datacenter mainstays as servers, storage, networking infrastructure, clusters, and converged solutions. These challenges include the lack of easy-to-run benchmarks, the complexity and cost of the equipment (multi-tier servers, large amounts of storage, and fast networks) necessary to run tests, and confusion about best testing practices.

PT has a lot of expertise in measuring datacenter performance, as you can tell from the hundreds of datacenter-focused test reports on our website. We see great potential in our working with the BenchmarkXPRT Development Community to help in this area. It is very possible that, as with AIXPRT, our approach to datacenter benchmarks would differ from the approach we’ve taken with previous benchmarks. While we have ideas for useful benchmarks we might develop down the road, more immediate steps could be drafting white papers, developing testing guidelines, or working with vendors to set up a lab.

Right now, we’re trying to gauge the level of interest in having such tools and in helping us carry out these initiatives. What are the biggest challenges you face in datacenter-focused performance and suitability to task evaluations? Would you be willing to work with us in this area? We’d love to hear from you and will be reaching out to members of the community over the coming weeks.

As always, thanks for your help!

Bill

Posted in AI, AIXPRT, Benchmarking, Collaborative benchmark development, Datacenter, Future of performance evaluation, Networking, Performance benchmarking, Principled Technologies, Servers, Storage | Also tagged cluster, converged solutions, Data centers, networking, servers, storage

HDXPRT 4: A little lighter and a lot faster

By Justin Greene

on August 30, 2018

This week, we’re sharing a little more about the upcoming HDXPRT 4 Community Preview. Just like previous versions of HDXPRT, HDXPRT 4 will use trial versions of commercial applications to complete workload tasks. We will include installers for some of those programs, such as Audacity and HandBrake, in the HDXPRT installation package. For other programs, such as Adobe Photoshop Elements 2018 and CyberLink Media Espresso 7.5, users will need to download the necessary installers prior to testing using links and instructions that we will provide. The HDXPRT 4 installation package is just over 4.7 GB, slightly smaller than previous versions.

I can also report that the new version requires fewer pre-test configuration steps and a full test run takes much less time than before. Some systems that took over an hour to complete an HDXPRT 2014 run are completing HDXPRT 4 runs in about 25 minutes.

We’ll continue to provide more information as we get closer to releasing the community preview. If you’re interested in testing with HDXPRT 4 before the general release but have not yet joined the community, we invite you to join now. If you have any questions or comments about HDXPRT or the community, please contact us.

Justin

Posted in Application-based benchmarks, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Community Preview, HDXPRT, HDXPRT 4, HDXPRT development process, HDXPRT release cycle, Performance benchmarking | Also tagged Adobe, Audacity, BenchmarkXPRT, CyberLink, Handbrake, HDXPRT, HDXPRT 4

AI and the next MobileXPRT

By Justin Greene

on August 16, 2018

As we mentioned a few weeks ago, we’re in the early planning stages for the next version of MobileXPRT—MobileXPRT 3. We’re always looking for ways to make XPRT benchmark workloads more relevant to everyday users, and a new version of MobileXPRT provides a great opportunity to incorporate emerging tech such as AI into our apps. AI is everywhere and is beginning to play a huge role in our everyday lives through smarter-than-ever phones, virtual assistants, and smart homes. The challenge for us is to identify representative mobile AI workloads that have the necessary characteristics to work well in a benchmark setting. For MobileXPRT, we’re researching AI workloads that have the following characteristics:

They work offline, not in the cloud.
They don’t require additional training prior to use.
They support common use cases such as image processing, optical character recognition (OCR), etc.

We’re researching the possibility of using Google’s Mobile Vision library, but there may be other options or concerns that we’re not aware of. If you have tips for places we should look, or ideas for workloads or APIs we haven’t mentioned, please let us know. We’ll keep the community informed as we narrow down our options.

Justin

Posted in AI, Android, Benchmark metrics, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Future of performance evaluation, Google, Machine learning, Mobile devices, MobileXPRT, Performance benchmarking | Also tagged AI, Google, image processing, mobile, MobileXPRT, optical character recognition

Planning the next version of MobileXPRT

By Justin Greene

on July 26, 2018

We’re in the early planning stages for the next version of MobileXPRT, and invite you to send us any suggestions you may have. What do you like or not like about MobileXPRT? What features would you like to see in a new version?

When we begin work on a new version of any XPRT, one of the first steps we take is to assess the benchmark’s workloads to determine whether they will provide value during the years ahead. This step almost always involves updating test content such as photos and videos to more contemporary file resolutions and sizes, and it can also involve removing workloads or adding completely new scenarios. MobileXPRT currently includes five performance scenarios (Apply Photo Effects, Create Photo Collages, Create Slideshow, Encrypt Personal Content, and Detect Faces to Organize Photos). Should we stick with these five or investigate other use cases? What do you think?

As we did with WebXPRT 3 and the upcoming HDXPRT 4, we’re also planning to update the MobileXPRT UI to improve the look of the benchmark and make it easier to use.

Crucially, we’ll also build the app using the most current Android Studio SDK. Android development has changed significantly since we released MobileXPRT 2015 and apps must now conform to stricter standards that require explicit user permission for many tasks. Navigating these changes shouldn’t be too difficult, but it’s always possible that we’ll encounter unforeseen challenges at some point during the process.

Do you have suggestions for test scenarios that we should consider for MobileXPRT? Are there existing features we should remove? Are there elements of the UI that you find especially useful or have ideas for improving? Please let us know. We want to hear from you and make sure that MobileXPRT continues to meet your needs.

Justin

Posted in Android, Benchmark metrics, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Mobile devices, MobileXPRT, MobileXPRT 2015, MobileXPRT 3, Phones, Tablets | Also tagged Android, benchmarks, mobile, MobileXPRT, MobileXPRT 2015, MobileXPRT 3, phones, photos, tablets

The WebXPRT 3 results calculation white paper is now available

By Justin Greene

on May 31, 2018

As we’ve discussed in prior blog posts, transparency is a core value of our open development community. A key part of being transparent is explaining how we design our benchmarks, why we make certain development decisions, and how the benchmarks actually work. This week, to help WebXPRT 3 testers understand how the benchmark calculates results, we published the WebXPRT 3 results calculation and confidence interval white paper.

The white paper explains what the WebXPRT 3 confidence interval is, how it differs from typical benchmark variability, and how the benchmark calculates the individual workload scenario and overall scores. The paper also provides an overview of the statistical techniques WebXPRT uses to translate raw times into scores.

To supplement the white paper’s overview of the results calculation process, we’ve also published a spreadsheet that shows the raw data from a sample test run and reproduces the calculations WebXPRT uses.

The paper and spreadsheet are both available on WebXPRT.com and on our XPRT white papers page. If you have any questions about the WebXPRT results calculation process, please let us know, and be sure to check out our other XPRT white papers.

Justin

Posted in Benchmark metrics, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Browser-based benchmarks, Performance benchmarking, Web-based testing, WebXPRT, WebXPRT 3, What makes a good benchmark? | Also tagged WebXPRT, WebXPRT 3, white paper

Tag Archives: benchmark

Out with the old, and in with the new

XPRTs in the datacenter

HDXPRT 4: A little lighter and a lot faster

AI and the next MobileXPRT

Planning the next version of MobileXPRT

The WebXPRT 3 results calculation white paper is now available

Check out the other XPRTs: