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Category: Source code

The CloudXPRT Preview is almost here

Justin Greene
By Justin Greene
on June 4, 2020

We’re happy to announce that we’re planning to release the CloudXPRT Preview next week! After we take the CloudXPRT Preview installation and source code packages live, they will be freely available to the public via CloudXPRT.com and the BenchmarkXPRT GitHub repository. All interested parties will be able to publish CloudXPRT results. However, until we begin the formal results submission and review process in July, we will publish only results we produce in our own lab. We’ll share more information about that process and the corresponding dates here in the blog in the coming weeks.

We do have one change to report regarding the CloudXPRT workloads we announced in a previous blog post. The Preview will include the web microservices and data analytics workloads (described below), but will not include the AI-themed container scaling workload. We hope to add that workload to the CloudXPRT suite in the near future, and are still conducting testing to make sure we get it right.

If you missed the earlier workload-related post, here are the details about the two workloads that will be in the preview build:

  • In the web microservices workload, a simulated user logs in to a web application that does three things: provides a selection of stock options, performs Monte-Carlo simulations with those stocks, and presents the user with options that may be of interest. The workload reports performance in transactions per second, which testers can use to directly compare IaaS stacks and to evaluate whether any given stack is capable of meeting service-level agreement (SLA) thresholds.
  • The data analytics workload calculates XGBoost model training time. XGBoost is a gradient-boosting framework  that data scientists often use for ML-based regression and classification problems. The purpose of the workload in the context of CloudXPRT is to evaluate how well an IaaS stack enables XGBoost to speed and optimize model training. The workload reports latency and throughput rates. As with the web-tier microservices workload, testers can use this workload’s metrics to compare IaaS stack performance and to evaluate whether any given stack is capable of meeting SLA thresholds.

The CloudXPRT Preview provides OEMs, the tech press, vendors, and other testers with an opportunity to work with CloudXPRT directly and shape the future of the benchmark with their feedback. We hope that testers will take this opportunity to explore the tool and send us their thoughts on its structure, workload concepts and execution, ease of use, and documentation. That feedback will help us improve the relevance and accessibility of CloudXPRT testing and results for years to come.

If you have any questions about the upcoming CloudXPRT Preview, please feel free to contact us.

Justin

Posted in benchmark, Benchmark metrics, Benchmarking, BenchmarkXPRT, BenchmarkXPRT development community, Cloud, CloudXPRT, container scaling, Hosted cloud, Hybrid cloud, IaaS, Machine learning, microservices, Performance benchmarking, Source code, web microservices | 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 |

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

Justin Greene
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 , , , |

The AIXPRT source code is now public

Justin Greene
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 , , , |

The MobileXPRT 3 source code is now available

Justin Greene
By Justin Greene
on June 27, 2019

We’re excited to announce that the MobileXPRT 3 source code is now available to BenchmarkXPRT Development Community members!

Download the MobileXPRT 3 source here (login required).

We’ve also posted a download link on the MobileXPRT tab in the Members’ Area, where you will find instructions for setting up and configuring a local instance of MobileXPRT 3.

As part of our community model for software development, source code for each of the XPRTs is available to anyone who joins the community. If you’d like to review XPRT source code, but haven’t yet joined the community, we encourage you to join! Registration is quick and easy, and if you work for a company or organization with an interest in benchmarking, you can join the community for free. Simply fill out the form with your company e-mail address and select the option to be considered for a free membership. We’ll contact you to verify the address and then activate your membership.

If you have any other questions about community membership or XPRT source code, feel free to contact us. We look forward to hearing from you!

Justin

Posted in Android, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Mobile devices, MobileXPRT, MobileXPRT 3, Open development, Performance testing on tablets, Source code | Tagged , , , , , , |

Transparent goals

Justin Greene
By Justin Greene
on May 16, 2019

Recently, Forbes published an article discussing a new report on phone battery life from Which?, a UK consumer advocacy group. In the report, Which? states that they tested the talk time battery life of 50 phones from five brands. During the tests, phones from three of the brands lasted longer than the manufacturers’ claims, while phones from another brand underperformed by about five percent. The fifth brand’s published battery life numbers were 18 to 51 percent higher than Which? recorded in their tests.

Folks can read the article for more details about the tests and the brands. While the report raises some interesting questions, and the article provides readers with brief test methodology descriptions from Which? and one manufacturer, we don’t know enough about the tests to say which set of claims is correct. Any number of variables related to test workloads or device configuration settings could significantly affect the results. Both parties may be using sound benchmarking principles in good faith, but their test methodologies may not be comparable. As it is, we simply don’t have enough information to evaluate the study.

Whether the issue is battery life or any other important device spec, information conflicts, such as the one that the Forbes article highlights, can leave consumers scratching their heads, trying to decide which sources are worth listening to. At the XPRTs, we believe that the best remedy for this type of problem is to provide complete transparency into our testing methodologies and development process. That’s why our lab techs verify all the hardware specs for each XPRT Weekly Tech Spotlight entry. It’s why we publish white papers explaining the structure of our benchmarks in detail, as well as how the XPRTs calculate performance results. It’s also why we employ an open development community model and make each XPRT’s source code available to community members. When we’re open about how we do things, it encourages the kind of honest dialogue between vendors, journalists, consumers, and community members that serves everyone’s best interests.

If you love tech and share that same commitment to transparency, we’d love for you to join our community, where you can access XPRT source code and previews of upcoming benchmarks. Membership is free for anyone with a verifiable corporate affiliation. If you have any questions about membership or the registration process, please feel free to ask.

Justin

Posted in Battery life, Benchmark metrics, Benchmarking, Benchmarking computing devices, BenchmarkXPRT, BenchmarkXPRT development community, Collaborative benchmark development, Open development, Performance benchmarking, Source code, What makes a good benchmark?, White papers, XPRT Weekly Tech Spotlight | Tagged , , , , , , , |

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