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Using WebXPRT 3 to compare the performance of popular browsers

Justin Greene
By Justin Greene
on February 6, 2020

Microsoft recently released a new Chromium-based version of the Edge browser, and several tech press outlets have released reviews and results from head-to-head browser performance comparison tests. Because WebXPRT is a go-to benchmark for evaluating browser performance, PCMag, PCWorld, and VentureBeat, among others, used WebXPRT 3 scores as part of the evaluation criteria for their reviews.

We thought we would try a quick experiment of our own, so we grabbed a recent laptop from our Spotlight testbed: a Dell XPS 13 7930 running Windows 10 Home 1909 (18363.628) with an Intel Core i3-10110U processor and 4 GB of RAM. We tested on a clean system image after installing all current Windows updates, and after the update process completed, we turned off updates to prevent them from interfering with test runs. We ran WebXPRT 3 three times on six browsers: a new browser called Brave, Google Chrome, the legacy version of Microsoft Edge, the new version of Microsoft Edge, Mozilla Firefox, and Opera. The posted score for each browser is the median of the three test runs.

As you can see in the chart below, five of the browsers (legacy Edge, Brave, Opera, Chrome, and new Edge) produced scores that were nearly identical. Mozilla Firefox was the only browser that produced a significantly different score. The parity among Brave, Chrome, Opera, and the new Edge is not that surprising, considering they are all Chromium-based browsers. The rank order and relative scaling of these results is similar to the results published by the tech outlets mentioned above.

Do these results mean that Mozilla Firefox will provide you with a speedier web experience? Generally, a device with a higher WebXPRT score is probably going to feel faster to you during daily use than one with a lower score. For comparisons on the same system, however, the answer depends in part on the types of things you do on the web, how the extensions you’ve installed affect performance, how frequently the browsers issue updates and incorporate new web technologies, and how accurately the browsers’ default installation settings reflect how you would set up the same browsers for your daily workflow.

In addition, browser speed can increase or decrease significantly after an update, only to swing back in the other direction shortly thereafter. OS-specific optimizations can also affect performance, such as with Edge on Windows 10 and Chrome on Chrome OS. All of these variables are important to keep in mind when considering how browser performance comparison results translate to your everyday experience. In such a competitive market, and with so many variables to consider, we’re happy that WebXPRT can help consumers by providing reliable, objective results.

What are your thoughts on today’s competitive browser market? We’d love to hear from you.

Justin

Posted in benchmark, Benchmarking, Browser-based benchmarks, Chrome OS, Cross-platform benchmarks, Google Chrome, Performance benchmarking, Web-based testing, WebXPRT, WebXPRT 3 | Also tagged , , , , , , , , ,

How to use alternate configuration files with AIXPRT

Justin Greene
By Justin Greene
on October 10, 2019

In last week’s AIXPRT Community Preview 3 announcement, we mentioned the new public GitHub repository that we’re using to publish AIXPRT-related information and resources. In addition to the installation readmes for each AIXPRT installation package, the repository contains a selection of alternative test config files that testers can use to quickly and easily change a test’s parameters.

As we discussed in previous blog entries about batch size, levels of precision, and number of concurrent instances, AIXPRT testers can adjust each of these key variables by editing the JSON file in the AIXPRT/Config directory. While the process is straightforward, editing each of the variables in a config file can take some time, and testers don’t always know the appropriate values for their system. To address both of these issues, we are offering a selection of alternative config files that testers can download and drop into the AIXPRT/Config directory.

In the GitHub repository, we’ve organized the available config files first by operating system (Linux_Ubuntu and Windows) and then by vendor (All, Intel, and NVIDIA). Within each section, testers will find preconfigured JSON files set up for several scenarios, such as running with multiple concurrent instances on a system’s CPU or GPU, running with FP32 precision instead of FP16, etc. The picture below shows the preconfigured files that are currently available for systems running Ubuntu on Intel hardware.

AIXPRT public repository snip 2

Because potential AIXPRT use cases cut across a wide range of hardware segments, including desktops, edge devices, and servers, not all AIXPRT workloads and configs will be applicable to each segment. As we move towards the AIXPRT GA, we’re working to find the best way to parse out these distinctions and communicate them to end users. In many cases, the ideal combination of test configuration variables remains an open question for ongoing research. However, we hope the alternative configuration files will help by giving testers a starting place.

If you experiment with an alternative test configuration file, please note that it should replace the existing default config file. If more than one config file is present, AIXPRT will run all the configurations and generate a separate result for each. More information about the config files and detailed instructions for how to handle the files are available in the EditConfig.md document in the public repository.

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

Justin

Posted in AI, AIXPRT, benchmark, Benchmark metrics, Collaborative benchmark development, Community Preview, GitHub, Intel, Linux, Machine learning, NVIDIA, Performance benchmarking, Ubuntu | Also tagged , , , , , , , , ,

A new HDXPRT 4 build is available!

Justin Greene
By Justin Greene
on July 18, 2019

A few weeks ago, we announced that a new HDXPRT 4 build, v1.1, was on the way. This past Monday, we published the build on HDXPRT.com.

The new build includes an updated version of HandBrake, the commercial application that HDXPRT uses for certain video conversion tasks. HandBrake 1.2.2 supports hardware acceleration with AMD Video Coding Engine (VCE), Intel Quick Sync, and the NVIDIA video encoder (NVENC). By default, HDXPRT4 v1.1 uses the encoder available through a system’s integrated graphics, but testers can target discrete graphics by changing a configuration file flag before running the benchmark. HDXPRT will then use the encoder provided by the discrete graphics hardware. This configuration setting takes effect only when more than one of the supported encoders (VCE, QSV, or NVENC) is present on the system.

As we mentioned before, in all other respects, the benchmark has not changed. That means that, apart from a scenario where a tester changes the targeted graphics hardware, scores from previous HDXPRT 4 builds will be comparable to those from the new build.

The updated HDXPRT 4 User Manual contains additional information and instructions for changing the configuration file flag. Please contact us if you have any questions about the new build. Happy testing!

Justin

Posted in AMD, benchmark, BenchmarkXPRT development community, graphics, HDXPRT, HDXPRT 4, NVIDIA, Performance benchmarking, Windows 10 | Also tagged , , , , , , , ,

Answering questions about the AIXPRT Community Preview

Justin Greene
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 , , , , , , , , , , ,

Preparing for the AIXPRT Community Preview

Bill Catchings
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 , , , , , , , , , , , , ,

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