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Contribute to WebXPRT’s AI capabilities with your NPU-equipped gear

A few weeks ago, we announced that we’re developing a new auxiliary WebXPRT 4 workload focused on local, browser-based AI technology. This is an exciting project for us, and as we work to determine the best approach from the perspective of frameworks, APIs, inference models, and test scenarios, we’re also thinking ahead to the testing process. To best understand how the new workload will impact system performance, we’re going to need to test it on hardware equipped with the latest generation of neural processing units (NPUs).

NPUs are not new, but the technology is advancing rapidly, and a growing number of PC and laptop manufacturers are releasing NPU-equipped systems. Several vendors have announced plans to release systems equipped with all-new NPUs in the latter half of this year. As is often the case with bleeding-edge technology, however, official release dates do not always coincide with widespread availability.

We want to evaluate new AI-focused WebXPRT workloads on the widest possible range of new systems, but getting a wide selection of gear equipped with the latest NPUs may take quite a while through normal channels. For that reason, we’ve decided to ask our readers for help to expedite the process.

If you’re an OEM or vendor representative with access to the latest generation of NPU-equipped gear and want to contribute to WebXPRT’s evolution, consider sending us any PCs, white boxes, laptops, 2-in-1s, or tablets (on loan) that would be suitable for NPU-focused testing. We have decades of experience serving as trusted testers of confidential and pre-release gear, so we’re well-acquainted with concerns about confidentiality that may come into play, and we won’t publish any information about the systems or related test results without your permission.

We will, though, be happy to share with you our test results on your systems, and we’d love to hear any guidance or other feedback from you on this new workload.

We’re open to any suitable gear, but we’re especially interested in AMD Ryzen AI, Apple M4, Intel Lunar Lake and Arrow Lake, and Qualcomm Snapdragon X Elite systems.

If you’re interested in sending us gear for WebXPRT development testing, please contact us. We’ll work out all the necessary details. Thanks in advance for your help!

Justin

Local AI and new frontiers for performance evaluation

Recently, we discussed some ways the PC market may evolve in 2024, and how new Windows on Arm PCs could present the XPRTs with many opportunities for benchmarking. In addition to a potential market shakeup from Arm-based PCs in the coming years, there’s a much broader emerging trend that could eventually revolutionize almost everything about the way we interact with our personal devices—the development of local, dedicated AI processing units for consumer-oriented tech.

AI already impacts daily life for many consumers through technologies such as such as predictive text, computer vision, adaptive workflow apps, voice recognition, smart assistants, and much more. Generative AI-based technologies are rapidly establishing a permanent, society-altering presence across a wide range of industries. Aside from some localized inference tasks that the CPU and/or GPU typically handle, the bulk of the heavy compute power that fuels those technologies has been in the cloud or in on-prem servers. Now, several major chipmakers are working to roll out their own versions of AI-optimized neural processing units (NPUs) that will enable local devices to take on a larger share of the AI load.

Examples of dedicated AI hardware in recently-released or upcoming consumer devices include Intel’s new Meteor Lake NPU, Apple’s Neural Engine for M-series SoCs, Qualcomm’s Hexagon NPU, and AMD’s XDNA 2 architecture. The potential benefits of localized, NPU-facilitated AI are straightforward. On-device AI could reduce power consumption and extend battery life by offloading those tasks from the CPUs. It could alleviate certain cloud-related privacy and security concerns. Without the delays inherent in cloud queries, localized AI could execute inference tasks that operate much closer to real time. NPU-powered devices could fine-tune applications around your habits and preferences, even while offline. You could pull and utilize relevant data from cloud-based datasets without pushing private data in return. Theoretically, your device could know a great deal about you and enhance many areas of your daily life without passing all that data to another party.

Will localized AI play out that way? Some tech companies envision a role for on-device AI that enhances the abilities of existing cloud-based subscription services without decoupling personal data. We’ll likely see a wide variety of capabilities and services on offer, with application-specific and SaaS-determined privacy options.

Regardless of the way on-device AI technology evolves in the coming years, it presents an exciting new frontier for benchmarking. All NPUs will not be created equal, and that’s something buyers will need to understand. Some vendors will optimize their hardware more for computer vision, or large language models, or AI-based graphics rendering, and so on. It won’t be enough for business and consumers to simply know that a new system has dedicated AI processing abilities. They’ll need to know if that system performs well while handling the types of AI-related tasks that they do every day.

Here at the XPRTs, we specialize in creating benchmarks that feature real-world scenarios that mirror the types of tasks that people do in their daily lives. That approach means that when people use XPRT scores to compare device performance, they’re using a metric that can help them make a buying decision that will benefit them every day. We look forward to exploring ways that we can bring XPRT benchmarking expertise to the world of on-device AI.

Do you have ideas for future localized AI workloads? Let us know!

Justin

The evolving PC market brings new opportunities for WebXPRT

Here at the XPRTs, we have to spend time examining what’s next in the tech industry, because the XPRTs have to keep up with the pace of innovation. In our recent discussions about 2024, a major recurring topic has been the potential impact of Qualcomm’s upcoming line of SOCs designed for Windows on Arm PCs.

Now, Windows on Arm PCs are certainly not new. Since Windows RT launched on the Arm-based Microsoft Surface RT in 2012, various Windows on Arm devices have come and gone, but none of them—except for some Microsoft SQ-based Surface devices—have made much of a name for themselves in the consumer market.

The reasons for these struggles are straightforward. While Arm-based PCs have the potential to offer consumers the benefits of excellent battery life and “always-on” mobile communications, the platform has historically lagged Intel- and AMD-based PCs in performance. Windows on Arm devices have also faced the challenge of a lack of large-scale buy-in from app developers. So, despite the past involvement of device makers like ASUS, HP, Lenovo, and Microsoft, the major theme of the Windows on Arm story has been one of very limited market acceptance.

Next year, though, the theme of that story may change. If it does, WebXPRT 4 is well-positioned to play an important part.

At the recent Qualcomm Technology Summit, the company unveiled the new 4nm Snapdragon X Elite SOC, which includes an all-new 12-core Oryon CPU, an integrated Adreno GPU, and an integrated Hexagon NPU (neural processing unit) designed for AI-powered applications. Company officials presented performance numbers that showed the X Elite surpassing the performance of late-gen AMD, Apple, and Intel competitor platforms, all while using less power.

Those are massive claims, and of course the proof will come—or not—only when systems are available for test. (In the past, companies have made similar claims about Windows on Arm advantages, only to see those claims evaporate by the time production devices show up on store shelves.)

Will Snapdragon X Elite systems demonstrate unprecedented performance and battery life when they hit the market? How will the performance of those devices stack up to Intel’s Meteor Lake systems and Apple’s M3 offerings? We don’t yet know how these new devices may shake up the PC market, but we do know that it looks like 2024 will present us with many golden opportunities for benchmarking. Amid all the marketing buzz, buyers everywhere will want to know about potential trade-offs between price, power, and battery life. Tech reviewers will want to dive into the details and provide useful data points, but many traditional PC benchmarks simply won’t work with Windows on ARM systems. As a go-to, cross-platform favorite of many OEMs—that runs on just about anything with a browser—WebXPRT 4 is in a perfect position to provide reviewers and consumers with relevant performance comparison data.

It’s quite possible that 2024 may be the biggest year for WebXPRT yet!

Justin

A new HDXPRT 4 build is available!

A few weeks ago, we announced that a new HDXPRT 4 build, v1.1, was on the way. This past Monday, we published the build on HDXPRT.com.

The new build includes an updated version of HandBrake, the commercial application that HDXPRT uses for certain video conversion tasks. HandBrake 1.2.2 supports hardware acceleration with AMD Video Coding Engine (VCE), Intel Quick Sync, and the NVIDIA video encoder (NVENC). By default, HDXPRT4 v1.1 uses the encoder available through a system’s integrated graphics, but testers can target discrete graphics by changing a configuration file flag before running the benchmark. HDXPRT will then use the encoder provided by the discrete graphics hardware. This configuration setting takes effect only when more than one of the supported encoders (VCE, QSV, or NVENC) is present on the system.

As we mentioned before, in all other respects, the benchmark has not changed. That means that, apart from a scenario where a tester changes the targeted graphics hardware, scores from previous HDXPRT 4 builds will be comparable to those from the new build.

The updated HDXPRT 4 User Manual contains additional information and instructions for changing the configuration file flag. Please contact us if you have any questions about the new build. Happy testing!

Justin

An updated HDXPRT 4 build is on the way

HandBrake recently released a new version, v1.2.2, of their video conversion software. Among other improvements, the new version includes support for certain AMD (VCE) and NVIDIA (NVENC) hardware-accelerated video encoders. Because we include HandBrake as one of the commercial applications in the HDXPRT installer package, and because we want to keep HDXPRT 4 up-to-date for testers, we’ve put together a new HDXPRT 4 build: v1.1.  It includes HandBrake 1.2.2’s new capabilities, and we’re currently testing it in the lab.

With the new build, testers will be able to choose whether HDXPRT’s HandBrake tasks target a system’s integrated or discrete graphics cards by changing a flag called “UseIntegrated” in the config file. In HDXPRT 4 v1.1, the flag is set to “true” by default, directing HandBrake to use the codec provided by the system’s integrated graphics hardware. On the other hand, if a system has both integrated and discrete graphics available, and a user sets the flag to “false,” HandBrake will use the codec provided by the discrete graphics.

This update allows users to compare the video conversion performance of different video codecs on the same system. In all other respects, the benchmark has not changed. So apart from a scenario where a tester changes the targeted graphics hardware, scores from previous HDXPRT 4 builds will be comparable to those from the new build.

We’ll let the community know as soon as the new build is available, and we’ll update the HDXPRT 4 User Manual to reflect the changes.

If you have any questions about the upcoming HDXPRT 4 build, please let us know!

Justin

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