Tag Archives: Community Preview

An update on AIXPRT development

on May 2, 2019

It’s been almost two months since the AIXPRT Community Preview went live, and we want to provide folks with a quick update. Community Preview periods for the XPRTs generally last about a month. Because of the complexity of AIXPRT and some of the feedback we’ve received, we plan to release a second AIXPRT Community Preview (CP2) later this month.

One of the biggest additions in CP2 will be the ability to run AIXPRT on Windows. AIXPRT currently requires test systems to run Ubuntu 16.04 LTS. This is fine for testers accustomed to Linux environments, but presents obstacles for those who want to test in a traditional Windows environment. We will not be changing the tests themselves, so this update will not influence existing results from Ubuntu. We plan to make CP2 available for download from the BenchmarkXPRT website for people who don’t wish to deal with GitHub.

Also, after speaking with testers and learning more about the kinds of data points people are looking for in AIXPRT results, we’ve decided to make significant adjustments to the AIXPRT results viewer. To make it easier for visitors to find what they’re looking for, we’ll add filters for key categories such as batch size, toolkit, and latency percentile (e.g., 50th, 90th, 99th), among others. We’ll also allow users to set desired ranges for metrics such as throughput and latency.

Finally, we’re adding a demo mode that displays some images and other information on the screen while a test is running to give users a better idea what is happening. While we haven’t seen results change while running in demo mode, users should not publish demo results or use them for comparison.

We hope to release CP2 in the second half of May and a GA version in mid-June. However, this project has more uncertainties than we usually encounter with the XPRTs, so that timeline could easily change.

We’ll continue to keep everyone up to date with AIXPRT news here in the blog. As always, we appreciate your suggestions. If you have any questions or comments about AIXPRT, please let us know.

Bill

Posted in AI, AIXPRT, Benchmarking, BenchmarkXPRT development community, Collaborative benchmark development, Community Preview, Cross-platform benchmarks, Future of performance evaluation, Linux, Machine learning, OpenVINO, Performance benchmarking, TensorFlow, TensorRT, Ubuntu | Also tagged AI, AIXPRT, Ubuntu, Windows

Answering questions about the AIXPRT Community Preview

By Justin Greene

on March 21, 2019

Over the last two weeks, we’ve received a few questions about the AIXPRT Community Preview. Specifically, community members have asked about the project’s focus, possible future steps, and the results table. We decided to answer each of these here in the blog, since others are likely to have the same questions. We encourage folks to submit any new questions they may have.

PT previously stated that AIXPRT would be focused on edge devices. The current published results are from desktops and laptops. Is the focus of AIXPRT changing?

In the past, we did say that the focus of AIXPRT would be edge inference devices. After much feedback, we’ve come to understand that focus is probably too restrictive. PCs and laptops are using inference machine learning, and a decent amount of inference is taking place on servers in the cloud until phones are capable enough to handle the workloads. We now see all of these devices as potential targets for AIXPRT.

How did you choose the current results in your database?

We ran the AIXPRT CP on some of the systems we used during development and testing. We will continue to publish additional results as we test available systems in our lab. We’d love to get results from the community that cover a wider base of devices.

Will you be publishing results from servers?

We welcome server results submissions from the community, and will review them for publication on our site.

Will AIXPRT ever be available for Windows systems?

This is a possibility we’re actively exploring, and we hope to be able to share more about it soon.

What’s the best way to navigate the results table?

AIXPRT can run three toolkits, utilize two networks, and target CPU or GPU hardware. Together, these configuration options produce a lot of data points. To make it easier to handle all these variables, we’re working to improve the navigation, sorting, and filtering capabilities of the results table. In the meantime, a few tips:

There are two tabs at the top of the table, one for the ResNet-50 network and one for the SSD-MobileNet network. You can click the tabs to move between results for these networks.
Clicking any of the column headers will sort the data in that column A-Z (with the first click) or Z-A (with a second click).
To see if an individual test targeted a system’s CPU or GPU, read the description in the Summary column, e.g. Intel Core i7-7600U GPU / OpenVINO.
Clicking the entry in the Source column will take you to a more detailed page listing additional test configuration and system hardware information.

We’ll continue to share more information about AIXPRT in the coming weeks. Do you have additional questions or comments about AIXPRT? Let us know.

Justin

Posted in Uncategorized | Also tagged AI, AIXPRT, BenchmarkXPRT, cloud, desktop, Intel, laptop, machine learning, OpenVINO, PCs, phone, server

All about the AIXPRT Community Preview

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 | Also tagged AI, AIXPRT, artificial intelligence, benchmark, machine learning, OpenVINO, TensorFlow, TensorRT

Preparing for the AIXPRT Community Preview

By Bill Catchings

on February 21, 2019

Thanks to everyone who downloaded the AIXPRT Request for Comments (RFC) preview build. Next week, we’re planning to publish the AIXPRT Community Preview (CP). 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. As with the RFC build, the test systems must be running Ubuntu 16.04 LTS. The minimum CPU and GPU requirements vary according to the toolkit being used, and we will publish more details about the hardware minimums next week.

As with our other community previews, we think the AIXPRT CP candidate is solid enough to allow folks to start quoting test results. During CP periods, we generally allow members to publish their own results, but wait until the build is available to the public before we post results on our site. Because community feedback is especially important for AIXPRT, we will handle things a bit differently. During the CP period, we’ll publish results that we produce as well as those from other members of the community, which you’ll be able to view at AIXPRT.com.

We’ll also provide detailed instructions for publishing results and sending them to us. Because of the high number of variables in each potential test configuration, we’ll ask testers to disclose more test, software, and hardware information than in the past. We will make this information available along with the results on AIXPRT.com. Our goal is that others can reproduce these numbers and confirm that they get similar results.

Our CP periods typically last four to six weeks before we make the benchmark available to the general public. If that schedule holds, it would place the public AIXPRT release around the end of March. During the CP period, we welcome your thoughts and suggestions about all aspects of the benchmark.

Also, we normally restrict access to our CPs to BenchmarkXPRT Development Community members. However, because we’re seeking broad input from experts in this field, we’ll gladly make the CP available to anyone interested in participating who has a GitHub account. To gain access, 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.

Please let us know if you have any questions. We look forward to hearing your feedback.

Bill

Posted in Uncategorized | Also tagged AI, AIXPRT, BenchmarkXPRT, BenchmarkXPRT Development Community, GitHub, Intel, machine learning, MobileNet, NVIDIA, OpenVINO, ResNet, TensorFlow, TensorRT, test

HDXPRT 4: Getting it right

By Justin Greene

on November 8, 2018

For BenchmarkXPRT Development Community members anticipating the HDXPRT 4 Community Preview (CP), we want to thank you for your patience and explain where we are in the release process.

This past month has brought a flurry of activity in the Windows 10 development world. We’ve been testing HDXPRT 4 extensively on each of the new prerelease builds available through the Windows Insider Program. While testing on a recent Windows 10 Redstone 5 preview build, we began to see inconsistent HDXPRT 4 workload scores on some systems. The difference between those workload scores and scores on the same systems with previous Windows 10 builds was significant enough for us to decide that the best course of action is to hold off on the CP until we understand the issue. We don’t want to release a CP only to run into serious problems with an imminent Windows release. We want to take the time to figure out what’s going on and get it right.

We hope to resolve these issues and publish the HDXPRT 4 CP as soon as possible. Thanks again for your patience. We’ll update the community soon with more information on the anticipated release schedule.

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, Windows 10 | Also tagged BenchmarkXPRT Development Community, HDXPRT, HDXPRT 4, Windows, Windows 10

Tag Archives: Community Preview

An update on AIXPRT development

Answering questions about the AIXPRT Community Preview

All about the AIXPRT Community Preview

Preparing for the AIXPRT Community Preview

HDXPRT 4: Getting it right

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