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Category: Future of performance evaluation

More, faster, better: The future according to Mobile World Congress 2019

More is more data, which the trillions of devices in the coming Internet of Things will be pumping through our air into our (computing) clouds in hitherto unseen quantities.

Faster is the speed at which tomorrow’s 5G networks will carry this data—and the responses and actions from our automated assistants (and possibly overlords).

Better is the quality of the data analysis and recommendations, thanks primarily to the vast army of AI-powered analytics engines that will be poring over everything digital the planet has to say.

Swimming through this perpetual data tsunami will be we humans and our many devices, our laptops and tablets and smartphones and smart watches and, ultimately, implants. If we are to believe the promise of this year’s Mobile World Congress in Barcelona—and of course I do want to believe it, who wouldn’t?—the result of all of this will be a better world for all humanity, no person left behind. As I walked the show floor, I could not help but feel and want to embrace its optimism.

The catch, of course, is that we have a tremendous amount of work to do between where we are today and this fabulous future.

We must, for example, make sure that every computing node that will contribute to these powerful AI programs is up to the task. From the smartphone to the datacenter, AI will end up being a very distributed and very demanding workload. That’s one of the reasons we’ve been developing AIXPRT. Without tools that let us accurately compare different devices, the industry won’t be able to keep delivering the levels of performance improvements that we need to realize these dreams.

We must also think a lot about how to accurately measure all other aspects of our devices’ performance, because the demands this future will place on them are going to be significant. Fortunately, the always evolving XPRT family of tools is up to the task.

The coming 5G revolution, like all tech leaps forward before it, will not come evenly. Different 5G devices will end up behaving differently, some better and some worse. That fact, plus our constant and growing reliance on bandwidth, suggests that maybe the XPRT community should turn its attention to the task of measuring bandwidth. What do you think?

One thing is certain: we at the Benchmark XPRT Development Community have a role to play in building the tools necessary to test the tech the world will need to deliver on the promise of this exciting trade show. We look forward to that work.

All about the AIXPRT Community Preview

Last week, Bill discussed our plans for the AIXPRT Community Preview (CP). I’m happy to report that, despite some last-minute tweaks and testing, we’re close to being on schedule. We expect to take the CP build live in the coming days, and will send a message to community members to let them know when the build is available in the AIXPRT GitHub repository.

As we mentioned last week, the AIXPRT CP build includes support for the Intel OpenVINO, TensorFlow (CPU and GPU), and TensorFlow with NVIDIA TensorRT toolkits to run image-classification workloads with ResNet-50 and SSD-MobileNet v1 networks. The test reports FP32, FP16, and INT8 levels of precision. Although the minimum CPU and GPU requirements vary by toolkit, the test systems must be running Ubuntu 16.04 LTS. You’ll be able to find more detail on those requirements in the installation instructions that we’ll post on AIXPRT.com.

We’re making the AIXPRT CP available to anyone interested in participating, but you must have a GitHub account. To gain access to the CP, please contact us and let us know your GitHub username. Once we receive it, we’ll send you an invitation to join the repository as a collaborator.

We’re allowing folks to quote test results during the CP period, and we’ll publish results from our lab and other members of the community at AIXPRT.com. Because this testing involves so many complex variables, we may contact testers if we see published results that seem to be significantly different than those from comparable systems. During the CP period, On the AIXPRT results page, we’ll provide detailed instructions on how to send in your results for publication on our site. For each set of results we receive , we’ll disclose all of the detailed test, software, and hardware information that the tester provides. In doing so, our goal is to make it possible for others to reproduce the test and confirm that they get similar numbers.

If you make changes to the code during testing, we ask that you email us and describe those changes. We’ll evaluate if those changes should become part of AIXPRT. We also require that users do not publish results from modified versions of the code during the CP period.

We expect the AIXPRT CP period to last about four to six weeks, placing the public release around the end of March or beginning of April. In the meantime, we welcome your thoughts and suggestions about all aspects of the benchmark.

Please let us know if you have any questions. Stay tuned to AIXPRT.com and the blog for more developments, and we look forward to seeing your results!

JNG

Principled Technologies and the BenchmarkXPRT Development Community release HDXPRT 4, a benchmark designed to show how well Windows devices handle real-world media tasks

Durham, NC, February 25 — Principled Technologies and the BenchmarkXPRT Development Community have released HDXPRT 4, a free benchmark that gives objective information about how well Windows 10 devices handle common media-creation tasks. HDXPRT 4 uses real commercial applications, like Photoshop and MediaEspresso, to perform tasks based on three everyday scenarios: photo editing, video conversion, and music editing. After the test is finished, the tool provides an overall measure by generating a single performance score. Anyone can go to HDXPRT.com to compare existing performance results on a variety of devices, or to download the app for themselves.

“When we started working on HDXPRT 4, we knew we wanted to create a benchmark that accurately reflects the kind of work average consumers do when creating content on their PCs,” said Bill Catchings, co-founder of Principled Technologies, which administers the BenchmarkXPRT Development Community. “HDXPRT delivers clear results that make sense to the wide audience of buyers shopping for new Windows systems.”

HDXPRT is part of the BenchmarkXPRT suite of performance evaluation tools, which includes WebXPRT, MobileXPRT, TouchXPRT, CrXPRT, and BatteryXPRT. The XPRTs help users get the facts before they buy, use, or evaluate tech products such as computers, tablets, and phones.

To learn more about the BenchmarkXPRT Development Community, go to www.BenchmarkXPRT.com.

About Principled Technologies, Inc.
Principled Technologies, Inc. is a leading provider of technology marketing, as well as learning and development services. It administers the BenchmarkXPRT Development Community.

Principled Technologies, Inc. is located in Durham, North Carolina, USA. For more information, please visit www.PrincipledTechnologies.com.

Company Contact
Justin Greene
BenchmarkXPRT Development Community
Principled Technologies, Inc.
1007 Slater Road, Ste. 300
Durham, NC 27704

BenchmarkXPRTsupport@PrincipledTechnologies.com

Engaging AI

In December, we wrote about our recent collaboration with students from North Carolina State University’s Department of Computer Science. We challenged the students to create a software console that includes an intuitive user interface, computes a performance metric, and uploads results to our database. The specific objective was to make it easy for testers to configure and run an implementation of the TensorFlow framework. In general, we hoped that the end product would model some of the same basic functions we plan to implement with AIXPRT, our machine-learning performance evaluation tool, currently under development.

The students did an outstanding job, and we hope to incorporate some of their work into AIXPRT in the future. We’ve been calling the overall project “Engaging AI” because it produced a functional tool that can help users interact with TensorFlow, and it was the first time that the students had an opportunity to work with AI tools. You can read more details on the Engaging AI page. We also have a new video that describes the project, including the new skillsets our students acquired to achieve success.

engaging-ai-vid

Finally, interested BenchmarkXPRT Development Community members can access to the project’s source code and additional documentation on our XPRT Experiments page. We hope you’ll check it out!

Justin

MobileXPRT 3 is here!

We’re excited to announce that MobileXPRT 3 is now available to the public! MobileXPRT 3 is the latest version of our popular tool for evaluating the performance of Android devices. The BenchmarkXPRT Development Community has been using a community preview for several weeks, but now anyone can run the tool and publish their results.

Compatible with systems running Android 5.0 and above, MobileXPRT 3 includes the same performance workloads as MobileXPRT 2015 (Apply Photo Effects, Create Photo Collages, Create Slideshow, Encrypt Personal Content, and Detect Faces to Organize Photos), plus a new optical character recognition-based workload called Scan Receipts for Spreadsheet.

MobileXPRT 3 is available at MobileXPRT.com and on the Google Play Store. Alternatively, you can download the app using either of the links below:



After trying out MobileXPRT 3, please submit your scores here and send any comments to BenchmarkXPRTsupport@principledtechnologies.com. To see test results from a variety of systems, go to MobileXPRT.com and click View Results, where you’ll find scores from a variety of Android devices. We look forward to seeing your results!

Justin

An update on the AIXPRT Request for Comments preview

As we approach the end of the original feedback window for the AIXPRT Request for Comments preview build, we want to update folks on the status of the project and what to expect in the coming weeks.

First, thanks to those who’ve downloaded the AIXPRT OpenVINO package and sent in their questions and comments. We value your feedback, and it’s instrumental in making AIXPRT a better tool. We’re currently working through some issues with the TensorFlow and TensorRT packages, and hope to add support for those to the RFC preview build repository very soon.

We’re also hoping to have a full-fledged community preview (CP) ready in mid to late February. Like our other community previews, the AIXPRT CP would be solid enough to allow folks to start quoting numbers. We typically make our benchmarks available to the general public four to six weeks after the community preview period begins, so if that schedule holds, it would place the public AIXPRT release around the end of March.

In light of the schedule described above, you still have time to gain access to the AIXPRT RFC preview build and give your feedback, so let us know if you’d like to check it out. The installation and testing process can take less than an hour, but getting everything properly set up can take a few tries. We are hard at work trying to make that process more straightforward. We welcome your input on all aspects of the benchmark, including workloads, ease of use, metrics, scores, and reporting.

Thanks for your help!

Justin

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