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Category: Future of performance evaluation

All about the AIXPRT Community Preview

Justin Greene
By Justin Greene
on February 28, 2019

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 We also require that users do not publish results from modified versions of the code during the CP period.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

Posted in AI, AIXPRT, Benchmark metrics, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Community Preview, Future of performance evaluation, Machine learning, OpenVINO, Performance benchmarking, TensorFlow, TensorRT, Ubuntu | Tagged , , , , , , , , |

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

Justin Greene
By Justin Greene
on February 25, 2019

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

Posted in Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Future of performance evaluation, HDXPRT, HDXPRT 4, HDXPRT development process, HDXPRT metrics, HDXPRT Press Releases, Performance benchmarking, Press Releases, WebXPRT, Windows 10 | Tagged , , , , , , , |

Engaging AI

Justin Greene
By Justin Greene
on February 7, 2019

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

Posted in AI, AIXPRT, Benchmark metrics, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Education, Engaging AI, Future of performance evaluation, North Carolina State University, TensorFlow |

MobileXPRT 3 is here!

Justin Greene
By Justin Greene
on January 31, 2019

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

Posted in Android, Android L, Android M, Android N, Android O, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Community Preview, Future of performance evaluation, Google, Mobile devices, MobileXPRT, MobileXPRT 3, MobileXPRT 3, Performance benchmarking, Performance testing on tablets, Phones |

An update on the AIXPRT Request for Comments preview

Justin Greene
By Justin Greene
on January 24, 2019

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

Posted in AI, AIXPRT, Benchmark metrics, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Community Preview, Cross-platform benchmarks, Future of performance evaluation, OpenVINO, TensorFlow, TensorRT | Tagged , , , , , |

The HDXPRT 4 Community Preview is now available!

Justin Greene
By Justin Greene
on January 17, 2019

Today we’re releasing the HDXPRT 4 Community Preview (CP). Just like previous versions of HDXPRT, HDXPRT 4 uses trial versions of commercial applications to complete workload tasks. For some of those programs, such as Audacity and HandBrake, HDXPRT 4 includes installers in the HDXPRT installation package. For other programs, such as Adobe Photoshop Elements 2018 and CyberLink Media Espresso 7.5, users need to download the necessary installers prior to testing by using the links and instructions in the HDXPRT 4 User Manual.

In addition to the editing photos, editing music, and converting videos workloads from prior versions of the benchmark, HDXPRT 4 includes two new Photoshop Elements scenarios. The first utilizes an AI tool that corrects closed eyes in photos, and the second creates a single panoramic photo from seven separate photos.

HDXPRT 4 is compatible with systems running Windows 10, and the installation package is slightly smaller than previous versions at just over 4.7 GB.

Because this is a community preview, it is available only to community members, who may download the preview from the HDXPRT tab in the Members’ Area. Because we expect results from CP testing to be comparable to results from the general release, members may publish their CP test results.

After you try the CP, please send us your comments. If you send information that’s relevant to the entire community, we may post an anonymous version of your comments to the forum. Thanks for your participation!

Justin

Posted in AI, Application-based benchmarks, Benchmark metrics, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Community Preview, Future of performance evaluation, HDXPRT, HDXPRT 4, HDXPRT release cycle, Performance benchmarking, Windows 10 |

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