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Potential web technology additions for WebXPRT 4

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

XPRT collaborations: North Carolina State University

For those of us who work on the BenchmarkXPRT tools, a core goal is involving new contributors and interested parties in the benchmark development process. Adding voices to the discussion fosters the collaboration and innovation that lead to powerful benchmark tools with lasting relevance.

One vehicle for outreach that we especially enjoy is sponsoring a student project through North Carolina State University. Each semester, the Senior Design Center in the university’s Department of Computer Science partners with external companies and organizations to provide student teams with an opportunity to work on real-world programming projects. If you’ve followed the XPRTs for a while, you may remember previous student projects such as Nebula Wolf, a mini-game that shows how well different devices handle games, and VR Demo, a virtual reality prototype workload based on a room escape scenario.

This fall, a team of NC State students is developing a software console for automating machine learning tests. Ideally, the tool will let future testers specify custom workload combinations, compute a performance metric, and upload results to our database. The project will also assess the impact of the framework on performance scores. In fact, the console will perform many of the same functions we plan to implement with AIXPRT.

The students have worked very hard on the project, and have learned quite a bit about benchmarking practices and several new software tools. The project will wrap up in the next couple of weeks, and we’ll share additional details as soon as possible. Early next year, we’ll publish a video about the experience.

If you’d like to join the NC State students and hundreds of other XPRT community members in the future of benchmark development, please let us know!

Justin

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