The screenshot below shows the viewer as I use the filter tab to explore additional filter options, such processor vendor. The screenshot below shows the viewer after I used the device type drop-down filter to select only desktops. The viewer includes a drop-down menu that lets users quickly filter results by major device type categories, and a tab that with additional filtering options, such as browser type, processor vendor, and result source. If the source is an external publisher, usersĬan click the Source link to navigate to the original site. Source of the result is PT, users can click the Run info button to see the Name of the test device, and basic hardware disclosure information. Percentile rank (66 th) among the scores in the current display, the The example above, the banner shows the overall score (227), the score’s If the user clicks to select the highlighted bar, the bar turns dark blue, and the dark blue banner at the bottom of the viewer displays additional details about that result. To view a single result in detail, the user hovers over a bar until it turns white and a small popup window displays the basic details of the result. Each vertical bar in the graph represents the overall score of a single test result, with bars arranged from lowest to highest. The screenshot below shows the tool’s default display. The viewer currently displays over 460 results, and we add new entries each week. With the viewer, users can explore all of the PT-curated results that we’ve published on, find more detailed information about those results, and compare results from different devices. The viewer provides WebXPRT 4 users with an interactive, information-packed way to browse test results that is not available for earlier versions of the benchmark. Input we received during the WebXPRT 4 planning process.New visitors to our site may not be aware of the WebXPRT 4 results viewer and how to use it. We’ll provide an update here in the blog as soon as possible. If it looks as though that timeline will change significantly, Preview build in the second half of November, with a general release before theĮnd of the year. We’ll share more about this possible workload as we firm up the details. We are considering developing a new workload that would use an Angular or React.js to scroll through hundreds of messages. Similar use cases are becoming more prevalent in conversational bot systems, domain-specific document search tools, and various other educational applications. The workload would use Bidirectional Encoder Representations from Transformers (BERT) to answer questions about a given text. We are considering the addition of an NLP workload using ONNX Runtime and/or TensorFlowJS. We are not planning to change this workload. This workload uses regex, arrays, strings, and Web Workers to review DNA and spell-check an essay. We are planning to replace ASM.js with WASM for the Notes task and with WASM-based Tesseract for the OCR task. This workload uses ASM.js to sync notes, extract text from a scanned receipt using optical character recognition (OCR), and add the scanned text to a spending report. The only change we are considering is combining it with the Stock Option Pricing workload (above). Sales Graphs exercises HTML5 Canvas and SVG performance. This workload provides a web-based application displaying multiple views of sales data. The only change we are considering is combining it with the Sales Graphs workload (below). This workload calculates and displays graphic views of a stock portfolio using Canvas, SVG, and dygraph.js. We are planning to replace ConvNetJS with WebAssembly (WASM) for both tasks and are considering upgrading the images to higher resolutions. This workload currently uses the ConvNetJS neural network library to complete two tasks: (1) organizing five images and (2) classifying the five images in an album. The only change we are considering is adding We will only make this change if we can ensure that five iterations produceĮnhancement.
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