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How to automate your WebXPRT 4 testing

We’re excited about the ongoing upward trend in the number of completed WebXPRT 4 runs that we’re seeing each month. OEM and tech press labs are responsible for a significant amount of that growth, and many of them use WebXPRT’s automation features to complete large blocks of hands-off testing at one time. We realize that many new WebXPRT users may be unfamiliar with the benchmark’s automation tools, so we decided to provide a quick guide to WebXPRT automation in today’s blog. Whether you’re testing one or 1,000 devices, the instructions below can help save you some time.

WebXPRT 4 allows users to run scripts in an automated fashion and control test execution by appending parameters and values to the WebXPRT URL. Three parameters are available:

  • test type
  • test scenarios
  • results

Below, you’ll find a description of those parameters and instructions for how you can use them to automate your test runs.

Test type

The WebXPRT automation framework accounts for two test types: (1) the six core workloads, and (2) any experimental workloads we might add in future builds. There are currently no experimental tests in WebXPRT 4, so always set the test type variable to 1.

  • Core tests: 1

Test scenario

The test scenario parameter lets you specify which subtest workloads to run by using the following codes:

  • Photo enhancement: 1
  • Organize album using AI: 2
  • Stock option pricing: 4
  • Encrypt notes and OCR scan using WASM: 8
  • Sales graphs: 16
  • Online homework: 32

To run a single subtest workload, use its code. To run multiple workloads, use the sum of their codes. For example, to run Stock options pricing (4) and Encrypt notes and OCR scan (8), use the sum of 12. To run all core tests, use 63, the sum of all the individual test codes (1 + 2 + 4 + 8 + 16 + 32 = 63).

Results format

The results format parameter lets you select the format of the results:

  • Display the result as an HTML table: 1
  • Display the result as XML: 2
  • Display the result as CSV: 3
  • Download the result as CSV: 4

To use the automation feature, start with the URL https://www.principledtechnologies.com/benchmarkxprt/webxprt/2021/wx4_build_3_7_3, append a question mark (?), and add the parameters and values separated by ampersands (&). For example, to run all the core tests and download the results, you would use the following URL: https://principledtechnologies.com/benchmarkxprt/webxprt/2021/wx4_build_3_7_3/auto.php?testtype=1&tests=63&result=4

We hope WebXPRT 4’s automation features will make testing easier for you. If you have any questions about WebXPRT or the automation process, please feel free to ask!

Justin

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

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