Category: AI

The Introduction to AIXPRT white paper is now available!

on March 26, 2020

Today, we published the Introduction to AIXPRT white paper. The paper serves as an overview of the benchmark and a consolidation of AIXPRT-related information that we’ve published in the XPRT blog over the past several months. For folks who are completely new to AIXPRT and veteran testers who need to brush up on pre-test configuration procedures, we hope this paper will be a quick, one-stop reference that helps reduce the learning curve.

The paper describes the AIXPRT toolkits and workloads, adjusting key test parameters (batch size, level of precision, number of concurrent instances, and default number of requests), using alternate test configuration files, understanding and submitting results, and accessing the source code.

We hope that Introduction to AIXPRT will prove to be a valuable resource. Moving forward, readers will be able to access the paper from the Helpful Info box on AIXPRT.com and the AIXPRT section of our XPRT white papers page. If you have any questions about AIXPRT, please let us know!

Justin

Posted in AI, AIXPRT, benchmark, Machine learning, MXNet, ResNet-50, SSD-MobileNet v1, White papers | Tagged AIXPRT, batch size, concurrent instances, OpenVINO, precision, ResNet-50, SSD-MobileNet v1, TensorFlow, TensorRT, white paper, Wide and Deep |

Odds and ends

By Justin Greene

on March 19, 2020

Today, we want to share quick updates on a few XPRT topics.

In case you missed yesterday’s announcement, the CrXPRT 2 Community Preview (CP) is now available. BenchmarkXPRT Development Community members can access the preview using a direct link we’ve posted on the CrXPRT tab in the XPRT Members’ Area (login required). This tab also provides a link to the CrXPRT 2 CP user manual. You can find a summary of what’s new with CrXPRT 2 in last week’s blog. During the preview period, we allow testers to publish CP test scores. Note that CrXPRT 2 overall performance test scores and battery life measurements are not comparable to those from CrXPRT 2015.

We’ll soon be publishing our first AIXPRT whitepaper, Introduction to AIXPRT. It will summarize the AIXPRT toolkits and workloads; how to adjust test parameters such as batch size, levels of precision, and concurrent instances; how to use alternate test configuration files; and how to understand test results. When the paper is available, we’ll post it on the XPRT white papers page and make an announcement here in the blog.

Finally, in response to decreased downloads and usage of BatteryXPRT, we have ended support for the benchmark. We’re always monitoring usage of the XPRTs so that we can better direct our resources to the current needs of users. We’ve removed BatteryXPRT from the Google Play Store, but it is still available for download on BatteryXPRT.com.

If you have any questions about CrXPRT 2, AIXPRT, or BatteryXPRT, please let us know!

Justin

Posted in AI, AIXPRT, Battery life, BenchmarkXPRT, BenchmarkXPRT development community, Chrome OS, Chromebooks, CrXPRT, White papers | Tagged AI, AIXPRT, Android, BatteryXPRT, Chrome, CrXPRT, white paper |

Thinking ahead to WebXPRT 4

By Justin Greene

on March 5, 2020

It’s been about two years since we released WebXPRT 3, and we’re starting to think about the WebXPRT 4 development cycle. With over 529,000 runs to date, WebXPRT continues to be our most popular benchmark because it’s quick and easy to run, it runs on almost anything with a web browser, and it evaluates performance using the types of web technologies that many people use every day.

For each new version of WebXPRT, we start the development process by looking at browser trends and analyzing the feasibility of incorporating new web technologies into our workload scenarios. For example, in WebXPRT 3, we updated the Organize Album workload to include an image-classification task that uses deep learning. We also added an optical character recognition task to the Encrypt Notes and OCR scan workload, and introduced a new Online Homework workload that combined part of the DNA Sequence Analysis scenario with a writing sample/spell check scenario.

Here are the current WebXPRT 3 workloads:

Photo Enhancement: Applies three effects, each using Canvas, to two photos.
Organize Album Using AI: Detects faces and classifies images using the ConvNetJS neural network library.
Stock Option Pricing: Calculates and displays graphic views of a stock portfolio using Canvas, SVG, and dygraphs.js.
Encrypt Notes and OCR Scan: Encrypts notes in local storage and scans a receipt using optical character recognition.
Sales Graphs: Calculates and displays multiple views of sales data using InfoVis and d3.js.
Online Homework: Performs science and English assignment tasks using Web Workers and Typo.js spell check.

What new technologies or workload scenarios should we add? Are there any existing features we should remove? Would you be interested in an associated battery life test? We want to hear your thoughts and ideas about WebXPRT, so please tell us what you think!

Justin

Posted in AI, benchmark, Benchmark metrics, Benchmarking, BenchmarkXPRT, Browser-based benchmarks, Collaborative benchmark development, Cross-platform benchmarks, image classification, JavaScript, Performance benchmarking, WebXPRT, WebXPRT 3, What makes a good benchmark? | Tagged benchmark, browsers, WebXPRT, WebXPRT 3 |

Principled Technologies and the BenchmarkXPRT Development Community make the AIXPRT source code available to the public

By Justin Greene

on February 18, 2020

Durham, NC, February 18 — Principled Technologies and the BenchmarkXPRT Development Community release the source code for the AIXPRT benchmark to the public. AIXPRT is a free tool that allows users to evaluate a system’s machine learning inference performance by running common image-classification, object detection, and recommender system workloads.

“Publishing the AIXPRT source code is part of our commitment to making the XPRT development process as transparent as possible,” said Bill Catchings, co-founder of Principled Technologies, which administers the BenchmarkXPRT Development Community. “By allowing all interested parties to download and review our source code, we’re taking tangible steps to improve openness in the benchmarking industry.”

To access the AIXPRT source code, visit the AIXPRT GitHub repository at https://github.com/BenchmarkXPRT/AIXPRT.

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 v1 networks, as well as the MXNet™ toolkit with a Wide and Deep recommender system workload. The test reports FP32, FP16, and INT8 levels of precision.

To access AIXPRT, visit www.AIXPRT.com.

AIXPRT is part of the BenchmarkXPRT suite of performance evaluation tools, which includes WebXPRT, CrXPRT, MobileXPRT, TouchXPRT, and HDXPRT. The XPRTs help users get the facts before they buy, use, or evaluate tech products such as computers, tablets, and phones.

To learn more about the BenchmarkXPRT Development Community, go to www.BenchmarkXPRT.com or contact a BenchmarkXPRT Development Community representative directly by sending a message to BenchmarkXPRTsupport@PrincipledTechnologies.com.

About Principled Technologies, Inc.
Principled Technologies, Inc. is a leading provider of technology marketing, as well as learning and development services. It administers the BenchmarkXPRT Development Community.

Principled Technologies, Inc. is located in Durham, North Carolina, USA. For more information, please visit www.PrincipledTechnologies.com.

Company Contact
Justin Greene
BenchmarkXPRT Development Community
Principled Technologies, Inc.
1007 Slater Road, Ste. 300
Durham, NC 27704
BenchmarkXPRTsupport@PrincipledTechnologies.com

Posted in AI, AIXPRT, BenchmarkXPRT development community, Open Source, Press Releases, Source code | Tagged AI, AIXPRT, benchmark, source code |

The AIXPRT source code is now public

By Justin Greene

on February 13, 2020

This week, we have good news for AIXPRT testers: the AIXPRT source code is now available to the public via GitHub. As we’ve discussed in the past, publishing XPRT source code is part of our commitment to making the XPRT development process as transparent as possible. With other XPRT benchmarks, we’ve only made the source code available to community members. With AIXPRT, we have released the source code more widely. By allowing all interested parties, not just community members, to download and review our source code, we’re taking tangible steps to improve openness and honesty in the benchmarking industry and we’re encouraging the kind of constructive feedback that helps to ensure that the XPRTs continue to contribute to a level playing field.

Traditional open-source models encourage developers to change products and even take them in new and different directions. Because benchmarking requires a product that remains static to enable valid comparisons over time, we allow people to download the source code and submit potential workloads for future consideration, but we reserve the right to control derivative works. This discourages a situation where someone publishes an unauthorized version of the benchmark and calls it an “XPRT.”

We encourage you to download and review the source and send us any feedback you may have. Your questions and suggestions may influence future versions of AIXPRT. If you have any questions about AIXPRT or accessing the source code, please feel free to ask! Please also let us know if you think we should take this approach to releasing the source code with other XPRT benchmarks.

Justin

Posted in AI, AIXPRT, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Cross-platform benchmarks, GitHub, Open development, Open Source, Performance benchmarking, Source code | Tagged AI, AIXPRT, GitHub, source code |

The XPRT activity we have planned for first half of 2020

By Justin Greene

on January 23, 2020

Today, we want to let readers know what to expect from the XPRTs over the next several months. Timelines and details can always change, but we’re confident that community members will see CloudXPRT Community Preview (CP), updated AIXPRT, and CrXPRT 2 releases during the first half of 2020.

CloudXPRT

Last week, Bill shared some details about our new datacenter-oriented benchmark, CloudXPRT. If you missed that post, we encourage you to check it out and learn more about the need for a new kind of cloud benchmark, and our plans for the benchmark’s structure and metrics. We’re already testing preliminary builds, and aim to release a CloudXPRT CP in late March, followed by a version for general availability roughly two months later.

AIXPRT

About a month ago, we explained how the number of moving parts in AIXPRT will necessitate a different development approach than we’ve used for other XPRTs. AIXPRT will require more frequent updating than our other benchmarks, and we anticipate releasing the second version of AIXPRT by mid-year. We’re still finalizing the details, but it’s likely to include the latest versions of ResNet-50 and SSD-MobileNet, selected SDK updates, ease-of-use improvements for the harness, and improved installation scripts. We’ll share more detailed information about the release timeline here in the blog as soon as possible.

CrXPRT 2

As we mentioned in December, we’re working on CrXPRT 2, the next version of our benchmark that evaluates the performance and battery life of Chromebooks. You can find out more about how CrXPRT works both here in the blog and at CrXPRT.com.

We’re currently testing an alpha version of CrXPRT 2. Testing is going well, but we’re tweaking a few items and refining the new UI. We should start testing a CP candidate in the next few weeks, and will have firmer information for community members about a CP release date very soon.

We’re excited about these new developments and the prospect of extending the XPRTs into new areas. If you have any questions about CloudXPRT, AIXPRT, or CrXPRT 2, please feel free to ask!

Justin

Posted in AI, AIXPRT, benchmark, Benchmark metrics, BenchmarkXPRT, BenchmarkXPRT development community, Chromebooks, Cloud, CloudXPRT, Collaborative benchmark development, Community Preview, CrXPRT, Datacenter, ResNet-50, SSD-MobileNet v1 | Tagged AIXPRT, Chrome OS, Chromebooks, ChromeXPRT, CloudXPRT, CrXPRT, datacenter, ResNet-50, SSD-MobileNet v1 |

Category: AI

The Introduction to AIXPRT white paper is now available!

Odds and ends

Thinking ahead to WebXPRT 4

Principled Technologies and the BenchmarkXPRT Development Community make the AIXPRT source code available to the public

The AIXPRT source code is now public

The XPRT activity we have planned for first half of 2020

CloudXPRT

AIXPRT

CrXPRT 2

Check out the other XPRTs: