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AIXPRT’s unique development path

With four separate machine learning toolkits on their own development schedules, three workloads, and a wide range of possible configurations and use cases, AIXPRT has more moving parts than any of the XPRT benchmark tools to date. Because there are so many different components, and because we want AIXPRT to provide consistently relevant evaluation data [...]

Planning for the next CrXPRT

We’re currently planning the next version of CrXPRT, our benchmark that evaluates the performance and battery life of Chromebooks. If you’re unfamiliar with CrXPRT, you can find out more about how it works both here in the blog and at CrXPRT.com. If you’ve used CrXPRT, we’d love to hear any suggestions you may have. What do [...]

HDXPRT 4 v1.2 and the HDXPRT 4 source code package are available

This week, we have good news for HDXPRT 4 testers. A few weeks ago, we discussed the fact that Adobe removed the trial version of Adobe Photoshop Elements (PSE) 2018 from the PSE download page. HDXPRT 4 used PSE 2018 for the Edit Photos scenario, so this change meant that new HDXPRT testers would not be [...]

The XPRT Spotlight Black Friday Showcase helps you shop with confidence

Black Friday and Cyber Monday are almost here, and you may be feeling overwhelmed by the sea of tech gifts to choose from. The XPRTs are here to help. We’ve gathered the product specs and performance facts for some of the hottest tech devices in one convenient place—the XPRT Spotlight Black Friday Showcase. The Showcase is [...]

Understanding AIXPRT’s default number of requests

A few weeks ago, we discussed how AIXPRT testers can adjust the key variables of batch size, levels of precision, and number of concurrent instances by editing the JSON test configuration file in the AIXPRT/Config directory. In addition to those key variables, there is another variable in the config file called “total_requests” that has a different default [...]

AIXPRT is here!

We’re happy to announce that AIXPRT is now available to the public! AIXPRT includes support for the Intel OpenVINO, TensorFlow, and NVIDIA TensorRT toolkits to run image-classification and object-detection workloads with the ResNet-50 and SSD-MobileNet v1networks, as well as a Wide and Deep recommender system workload with the Apache MXNet toolkit. The test reports FP32, FP16, and [...]

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