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Tag Archives: AIXPRT

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

New XPRTs for the new year

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

MWCS18 and AIXPRT: a new video

A few weeks ago, Bill shared his first impressions from this year’s Mobile World Congress Shanghai (MWCS). “5G +” was the major theme, and there was a heavy emphasis on 5G + AI. This week, we published a video about Bill’s MWCS experience and the role that the XPRTs can play in evaluating emerging technologies such as 5G, AI, and VR. Check it out!

MWC Shanghai 2018: 5G, AI, VR, and the XPRTs

 

You can read more about AIXPRT development here. We’re still accepting responses to the AIXPRT Request for Comments, so if you would like to share your ideas on developing an AI/machine learning benchmark, please feel free to contact us.

Justin

 

Machine learning in 2018

We are almost to the end of 2017 and, as you have probably guessed, we will not have a more detailed proposal of our machine learning benchmark ready by the end of the year.

The key aspects of the benchmark proposal we wrote about a few months ago haven’t changed, but we are running behind schedule. We are still hoping to have the proposal ready in Q1 2018 and the tool based on that proposal later in the year. We will keep you posted.

In the meantime, we hope you enjoy as much as we did the recent CGP Grey tech video explanation of machine learning. There are actually two videos—the first one gives a general overview and then the second one does a better job of looking at the current state of machine learning. It talks mainly about the training aspects of machine learning rather than the inference aspects that we are looking into with AIXPRT/MLXPRT.

From all of us in the BenchmarkXPRT Development Community, we hope you and yours have a wonderful holiday and a great start to 2018!

Bill

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