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Category: Future of performance evaluation

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 |

New XPRTs for the new year

Justin Greene
By Justin Greene
on January 3, 2019

Happy 2019! January is already a busy time for the XPRTs, so we want to share a quick preview of what community members can expect in the coming months.

The MobileXPRT 3 community preview (CP) is still open, but draws to a close on January 18th. If you are not familiar with the updates and changes we implemented in the newest version of MobileXPRT, you can read more in the blog. Members can access this APK on the MobileXPRT tab in the Members’ Area. We also posted an installation guide that provides both a general overview of the app and detailed instructions for each step. The entire process takes about five minutes on most devices. If you haven’t already, give it a try!

We also recently published the first AIXPRT Request for Comments (RFC) preview build, an early version of one of the tools we’re developing to evaluate machine learning performance. You can find more details in Bill’s most recent blog post and on AIXPRT.com. Only BenchmarkXPRT Development Community members have access to our RFCs and the opportunity to provide feedback. However, because we’re seeking broad input from experts in this field, we’ll gladly make anyone interested in participating a member. To gain access to the AIXPRT repository, please send us a request.

Work on the HDXPRT 4 CP candidate build continues, and we hope to publish the preview for community members this month. We appreciate everyone’s patience as we work to get this right. We think it will be worth the wait.

On a general note, I’ll be travelling to CES 2019 in Las Vegas next week. CES is a great opportunity for us to survey emerging tech and industry trends, and I look forward to sharing my thoughts from the show. If you’ll be there and would like to discuss any aspect of the XPRTs in person, let me know.

Justin

Posted in AI, AIXPRT, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, CES, Collaborative benchmark development, Community Preview, Future of performance evaluation, HDXPRT, HDXPRT 4, HDXPRT development process, Machine learning, MobileXPRT, MobileXPRT 3, Performance benchmarking, Trade Shows | Tagged , , , , , , |

The AIXPRT Request for Comments preview build

Bill Catchings
By Bill Catchings
on December 20, 2018

In the next few days, we’ll be publishing the first AIXPRT tool as a Request for Comments (RFC) preview build, an early version of one of the AIXPRT tools we’re developing to help evaluate machine learning performance.

We’re inviting folks to run the workload and send in their thoughts and suggestions. Only BenchmarkXPRT Development Community members have access to our RFCs and the opportunity to provide feedback. However, because we’re seeking broad input from experts in this field, we’ll gladly make anyone interested in participating a member.

This AIXPRT RFC preview build includes support for the Intel OpenVINO computer vision toolkit to run image classification workloads with ResNet-50 and SSD-MobileNet v1 networks. The test reports FP32 and FP16 levels of precision. The system requirements are:

  • Operating system = Ubuntu 16.04
  • CPU = 6th to 8th generation Intel Core or Xeon processors, or Intel Pentium processors N4200/5, N3350/5, N3450/5 with Intel HD Graphics


We welcome input on all aspects of the benchmark, including scope, workloads, metrics and scores, user experience, and reporting. We will add support for TensorFlow and TensorRT to the AIXPRT RFC preview build during the preview period. We are accepting feedback through January 25th, 2019, after which we’ll collect and evaluate responses before publishing the next build. Because this is an RFC release, we ask that testers do not publish scores or use the results for comparison purposes.

We’ll send out a community announcement when the RFC preview build is officially available, and we’ll also post an announcement and RFC preview build user guide on AIXPRT.com. We’re hosting the AIXPRT RFC preview build in a dedicated GitHub repository, so please contact us at BenchmarkXPRTsupport@principledtechnologies.com to gain access.

This is just the next step for AIXPRT. With your help, we hope to add more workloads and other frameworks in the coming months. We look forward to receiving your feedback!

Bill

Posted in AI, AIXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Community Preview, Future of performance evaluation, Machine learning, Open development, OpenVINO, Performance benchmarking, TensorFlow, TensorRT, Ubuntu, What makes a good benchmark? |

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