BenchmarkXPRT Blog banner

Tag Archives: MobileNet

Preparing for the AIXPRT Community Preview

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

Check out the other XPRTs:

Forgot your password?