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Category: Collaborative benchmark development

Moving forward with WebXPRT 4

Justin Greene
By Justin Greene
on March 4, 2021

In the coming months, we’ll be moving forward with the first stages of the WebXPRT 4 development process. It’s been a while since we last asked readers to send their thoughts about web technologies and workloads that may be a good fit for WebXPRT 4, but we’re still very much open to ideas. If you missed our previous posts about possible changes for WebXPRT 4, we recap the most prominent ideas below. We also request specific feedback regarding a potential battery life component.

  • Community members have asked about a WebXPRT 4 battery life test. Any such test would likely be very similar to the performance-weighted battery life test in CrXPRT 2 (as opposed to a simple rundown test). While WebXPRT runs in almost any browser, cross-browser compatibility issues could cause a WebXPRT battery life test to run in only one browser. If this turned out to be the case, would you still be interested in using the battery life test? Please let us know.
  • One of the most promising ideas is the potential addition of one or more WebAssembly (WASM) workloads. WASM is a low-level, binary instruction format that works across all modern browsers. It offers web developers a great deal of flexibility and provides the speed and efficiency necessary for running complex client applications in the browser. WASM enables a variety of workload scenario options, including gaming, video editing, VR, virtual machines, image recognition, and interactive educational content.
  • We are also considering adding a web-based machine learning workload with TensorFlow for JavaScript (TensorFlow.js). TensorFlow.js offers pre-trained models for a wide range of tasks including image classification, object detection, sentence encoding, and natural language processing. We could also use this technology to enhance one of WebXPRT’s existing AI-themed workloads, such as Organize Album using AI or Encrypt Notes and OCR Scan.
  • Other ideas include using a WebGL-based workload to target GPUs, and simulating common web applications.

We’ll start work on WebXPRT 4 soon, but there’s still time to send your comments and ideas, so please do so as quickly as possible!

Justin

Posted in battery life, benchmark, BenchmarkXPRT, Browser-based benchmarks, Collaborative benchmark development, Future of performance evaluation, Performance benchmarking, TensorFlow, WebAssembly, WebGL, WebXPRT, WebXPRT 3 | Tagged , , , , , , , , , |

The CloudXPRT v1.1 beta is on the way

Justin Greene
By Justin Greene
on February 11, 2021

As we’ve been working on improvements and updates for CloudXPRT, we’ve been using feedback from community members to determine which changes will help testers most in the short term. To make some of those changes available to the community as soon as possible, we plan to release a beta version of CloudXPRT v1.1 in the coming weeks.

During the v1.1 beta period, the CloudXPRT v1.01 installation packages on CloudXPRT.com and our GitHub repository will continue to include the officially supported version of CloudXPRT. However, interested testers can experiment with the v1.1 beta version in new environments while we finalize the build for official release. 

The CloudXPRT v1.1 beta includes the following primary changes:

  • We’re adding support for Ubuntu 20.04.2 or later, the number one request we’ve received.
  • We’re consolidating and standardizing the installation packages for both workloads. Instead of one package for the data analytics workload and four separate packages for the web microservices workload, each workload will have two installation packages: one for all on-premises testing and one for testing with all three supported CSPs.
  • We’re incorporating Terraform to help create and configure VMs, which will help to prevent situations when testers do not allocate enough storage per VM prior to testing.
  • We use Kubespray to manage Kubernetes clusters, and Kubespray uses Calico as the default network plug in. Calico has not always worked well for CloudXPRT in the CSP environment, so we’re replacing Calico with Weave.


At the start of the beta period, we will share a link to the v1.1 beta download page here in the blog. You’ll be free to share this link. To avoid confusion, we will not add the beta download to the v1.01 downloads available on CloudXPRT.com.

As the beta release date approaches, we’ll share more details about timelines, access, and any additional changes to the benchmark. If you have any questions about the upcoming CloudXPRT v1.1 beta, please let us know!

Justin

Posted in benchmark, Benchmark metrics, BenchmarkXPRT, BenchmarkXPRT development community, Cloud, CloudXPRT, Clusters, Collaborative benchmark development, Cross-platform benchmarks, data analytics, Datacenter, GitHub, Hosted cloud, IaaS, Kubernetes, Linux, on premises, Performance benchmarking, web microservices | Tagged , , , , , , , , , |

Thinking ahead to the next HDXPRT

Justin Greene
By Justin Greene
on November 12, 2020

We’re currently formulating our 2021 development roadmap for the XPRTs. In addition to planning CloudXPRT and WebXPRT updates, we’re discussing the possibility of releasing HDXPRT 5 in 2021. It’s hard for me to believe, but it’s been about two and a half years since we started work on HDXPRT 4, and February 2021 will mark two years since the first HDXPRT 4 release. Windows PCs are more powerful than ever, so it’s a good time to talk about how we can enhance the benchmark’s ability to measure how well the latest systems handle real-world media technologies and applications.

When we plan a new version of an XPRT benchmark, one of our first steps is updating the benchmark’s workloads so that they will remain relevant in years to come. We almost always update application content, such as photos and videos, to contemporary file resolutions and sizes. For example, we added both higher-resolution photos and a 4K video conversion task in HDXPRT 4. Are there specific types of media files that you think would be especially relevant to high-performance media tasks over the next few years?

Next, we will assess the suitability of the real-world trial applications that the editing photos, editing music, and converting videos test scenarios use. Currently, these are Adobe Photoshop Elements, Audacity, CyberLink MediaEspresso, and HandBrake. Can you think of other applications that belong in a high-performance media processing benchmark?

In HDXPRT 4, we gave testers the option to target a system’s discrete graphics card during the video conversion workload. Has this proven useful in your testing? Do you have suggestions for new graphics-oriented workloads?

We’ll also strive to make the UI more intuitive, to simplify installation, and to reduce the size of the installation package. What elements of the current UI do you find especially useful or think we could improve? 

We welcome your answers to these questions and any additional suggestions or comments on HDXPRT 5. Send them our way!

Justin

Posted in Adobe, Application-based benchmarks, benchmark, BenchmarkXPRT, CloudXPRT, Collaborative benchmark development, Future of performance evaluation, HDXPRT, HDXPRT 4, HDXPRT development process, HDXPRT metrics, HDXPRT release cycle, Performance benchmarking, WebXPRT, What makes a good benchmark? | Tagged , , , , , , , , |

Potential web technology additions for WebXPRT 4

Justin Greene
By Justin Greene
on August 20, 2020

A few months ago, we invited readers to send in their thoughts and ideas about web technologies and workload scenarios that may be a good fit for the next WebXPRT. We’d like to share a few of those ideas today, and we invite you to continue to send your feedback. We’re approaching the time when we need to begin firming up plans for a WebXPRT 4 development cycle in 2021, but there’s still plenty of time for you to help shape the future of the benchmark.

One of the most promising ideas for WebXPRT 4 is the potential addition of one or more WebAssembly (WASM) workloads. WASM is a low-level, binary instruction format that works across all modern browsers. It offers web developers a great deal of flexibility and provides the speed and efficiency necessary for running complex client applications in the browser. WASM enables a variety of workload scenario options, including gaming, video editing, VR, virtual machines, image recognition, and interactive educational content.

In addition, the Chrome team is dropping Portable Native Client (PNaCL) support in favor of WASM, which is why we had to remove a PNaCL workload when updating CrXPRT 2015 to CrXPRT 2. We generally model CrXPRT workloads on existing WebXPRT workloads, so familiarizing ourselves with WASM could ultimately benefit more than one XPRT benchmark.

We are also considering adding a web-based machine learning workload with TensorFlow for JavaScript (TensorFlow.js). TensorFlow.js offers pre-trained models for a wide variety of tasks including image classification, object detection, sentence encoding, natural language processing, and more. We could also use this technology to enhance one of WebXPRT’s existing AI-themed workloads, such as Organize Album using AI or Encrypt Notes and OCR Scan.

Other ideas include using a WebGL-based workload to target GPUs and investigating ways to incorporate a battery life test. What do you think? Let us know!

Justin

Posted in AI, battery life, benchmark, BenchmarkXPRT, BenchmarkXPRT development community, Browser-based benchmarks, Collaborative benchmark development, Cross-platform benchmarks, image classification, Machine learning, object detection, Performance benchmarking, Virtual reality, Web-based testing, WebAssembly, WebGL, WebXPRT, WebXPRT 3, What makes a good benchmark? | Tagged , , , , , , , , , , , , |

Adapting to a changing tech landscape

Justin Greene
By Justin Greene
on April 23, 2020

The BenchmarkXPRT Development Community started almost 10 years ago with the development of the High Definition Experience & Performance Ratings Test, also known as HDXPRT. Back then, we distributed the benchmark to interested parties by mailing out physical DVDs. We’ve come a long way since then, as testers now freely and easily access six XPRT benchmarks from our site and major app stores.

Developers, hardware manufacturers, and tech journalists—the core group of XPRT testers—work within a constantly changing tech landscape. Because of our commitment to providing those testers with what they need, the XPRTs grew as we developed additional benchmarks to expand the reach of our tools from PCs to servers and all types of notebooks, Chromebooks, and mobile devices.

As today’s tech landscape continues to evolve at a rapid pace, our desire to play an active role in emerging markets continues to drive us to expand our testing capabilities into areas like machine learning (AIXPRT) and cloud-first applications (CloudXPRT). While these new technologies carry the potential to increase efficiency, improve quality, and boost the bottom line for companies around the world, it’s often difficult to decide where and how to invest in new hardware or services. The ever-present need for relevant and reliable data is the reason many organizations use the XPRTs to help make confident choices about their company’s future tech.

We just released a new video that helps to explain what the XPRTs provide and how they can play an important role in a company’s tech purchasing decisions. We hope you’ll check it out!

We’re excited about the continued growth of the XPRTs, and we’re eager to meet the challenges of adapting to the changing tech landscape. If you have any questions about the XPRTs or suggestions for future benchmarks, please let us know!

Justin

Posted in AI, AIXPRT, benchmark, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Chromebooks, Cloud, CloudXPRT, Collaborative benchmark development, Future of performance evaluation, HDXPRT, History of benchmarking, Performance benchmarking | Tagged , , , , , , |

News about the CloudXPRT source code

Justin Greene
By Justin Greene
on April 9, 2020

For much of the BenchmarkXPRT Development Community’s history, we offered community members exclusive access to XPRT benchmark source code. Back in February, we started to experiment with a different approach when we made the AIXPRT source code publicly available on GitHub. By allowing anyone who is interested in AIXPRT to download and review the source code, we reinforced our commitment to making the XPRT development process as transparent as possible. We also want the XPRTs to continue to contribute to fair practices in the benchmarking world, and we believe that expanded access to the source code encourages constructive feedback to help in this goal.

The feedback we received after publishing the AIXPRT source code was very positive; thank you to all who reached out. Because of that feedback and our desire to increase openness, we’ve decided use standard open source licenses to make the CloudXPRT source code available to the public when we release of the first build, or shortly thereafter. As with AIXPRT, folks will be able to download the CloudXPRT source code and submit potential workloads for future consideration, but we reserve the right to control derivative works.

We’ll share more information about the first CloudXPRT release and its source code in the coming weeks. If you have any questions about XPRT source code, feel free to ask.  We also welcome any thoughts about using this approach to release the source code of other XPRT benchmarks. As always, feel free to comment below or reach out by email.

Justin

Posted in AI, AIXPRT, benchmark, BenchmarkXPRT, BenchmarkXPRT development community, Cloud, CloudXPRT, Collaborative benchmark development, Open development, Open Source, Source code |

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