What’s better than testing your artificial intelligence (AI) application on virtualized hardware? Testing on real hardware.
Intel® DevCloud™ provides access to real world hardware platforms hosted by Intel. In a few clicks, developers are able to gain remote access to physical systems in order to benchmark their deep learning and artificial intelligence applications.
Optimize your AI Application OnLogic
Now developers are able to optimize their applications and benchmark them on OnLogic industrial hardware with Intel DevCloud. Choose from our popular Helix 500 system or the latest addition to our ML series, the ML100G-53.
Perform your AI Testing on the Helix 500
One of our most popular systems, the Helix 500, is available in two configurations on DevCloud. The first features an Intel Core i9-10900T processor, while the second system offers an Intel Core i7-10700T. Both systems feature Intel UHD Graphics 630 and 32GB of RAM.
For AI Developers – Right Size your AI Application Hardware
The ability to test two similar systems highlights one of the primary benefits of DevCloud; Right-sizing your hardware and application performance. An AI developer can run their application on real world hardware with similar specs in order to determine whether the features offered by the more costly Core i9 processor are beneficial. They might discover that the Core i7 processor is capable of meeting their performance requirements.
An AI developer may also make the decision to refine their application based on the performance of a specific system. Modifying the application to perform well on lower-cost hardware could have a significant impact on the overall cost of launching their solution. Especially if looking to deploy devices at a large scale.
Perform your AI Test on the ML100G-53
The ML100G-53 features the 11th generation of Intel Core processors, formerly known as Tiger Lake. This new generation offers a substantial increase in performance through powerful Intel Iris Xe integrated graphics. However, when utilizing Intel’s OpenVINO toolkit the ML100G-53 is really able to shine in AI applications.
For AI Developers – Leverage OpenVINO
An AI Developer is able to run their workloads on a CPU equipped with Intel Xe Integrated Graphics. This brings the similar horsepower of a discrete GPU for Artificial Intelligence and Machine Learning applications. By combining their processing power, OpenVINO can significantly increase the speed at which an application processes data. DevCloud includes access to the OpenVINO toolkit. You can really dig into the details by visiting Intel’s Artificial Intelligence blog post.
When combined with fanless thermal management, the ML100G-53 offers the ability to perform Artificial Intelligence and Machine Learning in challenging environments that may cause traditional fanned systems to fail. The fanless and ventless design prevents the ingress of dust and debris into the system, increasing reliability.
Get Started with Intel DevCloud
We’ve reviewed a few of the high level benefits of Intel DevCloud and introduced you to the OnLogic hardware that is now available on the platform. So how can you take advantage of this valuable service?
Start by enrolling as a user on the DevCloud website. Once you’re signed up and logged in, you can visit the OnLogic DevCloud page to select the system you’d like to run your application on. Upload your model or data and begin testing your models online.
If you’re seeking additional guidance on how to get started, DevCloud offers written tutorials to begin your journey with the platform. Referred to as “Jupyter notebooks,” they include helpful tips on coding and navigating the platform.
Real Word Development to Real World Deployment
When your application is ready to leave the cloud and deploy in the real world, you can depend on OnLogic industrial computers to be a reliable component of your solution stack.
To learn more about how our Industrial and Rugged systems may be the perfect fit for your deployment, contact a hardware specialist today!