Huawei Atlas AI Computing Platform: A Gift for Developers

In Greek mythology, Atlas was a titan condemned to hold up the celestial heavens for eternity after losing the series of battles known as the Titanomachy.

Unlike the Greek mythical gods that changed the world with their own power, individuals are flawed, meaning the human race must count on its collective wisdom to thrive. Environments where wisdom is shared have generated great feats such as the computer, the Internet, and artificial intelligence (AI), which have all lifted the human society to a new height.

In Greek mythology, Atlas protects the world by holding the sky on his shoulders. Tens of thousands of years later in 2019, the Huawei-developed Atlas AI computing platform was launched, which carries on the mission to push us into the cloud digital era.

Huawei

Let’s take a deeper look at the Huawei Atlas platform and its position in the marketplace.

The Huawei Atlas AI computing platform provides diverse product forms—such as modules, accelerator cards, edge stations, servers, and clusters—to help you build an all-scenario AI infrastructure solution across cloud-edge-device. Running on Huawei’s Ascend series AI processors and mainstream heterogeneous computing components, the platform is designed to help supercharge the industries of tomorrow, such as Safe City, Intelligent Transportation, Smart Healthcare, and AI inference.

The Atlas AI computing platform provides powerful AI computing for customers to handle massive data volumes. It plays an important role in the Huawei full-stack, all-scenario AI solution.

One of the highlights of the Atlas AI computing platform is the collaboration across edge-device-cloud.

The cloud is the core of the entire platform for computing and massive data processing. The Atlas 800 AI server provides a high-density, cloud-based AI inference solution that achieves better processing performance with fewer servers.

A typical application scenario of the Atlas 800 server is the urban governance system. For example, in a city with a population of over 20 million people and more than 3 million vehicles, approximately 43 million images of passing vehicles will be generated every day. This makes real-time traffic analysis a must for traffic governance. The data analytics of vehicles, traffic violations, and traffic flow requires powerful computing in the cloud.

To meet such requirements, either 3,000 servers equipped with general-purpose processors are needed, or 72 to 144 GPU-based servers. However, thanks to the neural processing unit (NPU) processors optimized for AI deep learning, only 60 Atlas 800 servers are required to do the same, greatly simplifying deployment and slashing power consumption. This is the advantage that the NPU-powered Atlas 800 AI server yields over its counterparts in intelligent traffic governance scenario.

Edge computing is a supplement to cloud computing. An open platform that integrates the capabilities of network, computing, storage, and application is deployed at the edge to provide services closer to end users. The proprietary Atlas 500 AI edge station and the Atlas 300 AI accelerator card boost the efficiency of edge AI inference, making it an ideal option for industrial quality inspection.

Enterprises in the manufacturing industry invest huge manpower in quality inspection. However, due to the intense workload and the dangerous work environments of some special manufacturing processes, the highest accuracy rate of quality inspection can reach only 90% with conventional infrastructure.

In recent years, machine-vision quality inspection in the manufacturing industry has increased the accuracy rate to about 95%, but a higher accuracy rate is still required. Many enterprises have purchased expensive equipment for fully automated quality inspection, but human labor is still needed for secondary quality inspection. In response to the industry requirements, Huawei has risen to the occasion to provide an AI industrial quality inspection solution.

Huawei collaborates with ADLINK Technology to integrate the Atlas 300 AI accelerator card into an industrial computer, providing AI capabilities for each sensor of the industrial computer. The supply chain application team at Huawei has developed cutting-edge AI algorithms based on neural networks such as SSD and U-Net, designed to offer an average quality inspection accuracy of 99%, and even up to 99.9% for some processes. Simple yet effective, this is the exciting achievement that will supercharge the manufacturing industry.

Devices such as drones, intelligent robots, and robotic arms in factories are more familiar to users. In a competitive market where vendors aim to make the fastest, most intelligent device, even the smallest improvements can help an enterprise make huge strides in the marketplace. The Huawei Atlas 200 AI accelerator module is specifically built to improve the performance of the most demanding device workloads.

In addition to the AI module that benefits terminal users, Huawei also empowers AI developers by launching the Atlas 200 DK AI Developer Kit (also known as Atlas 200 DK), which can be used by scientific researchers, universities, and individual developers.

With the Atlas 200 DK, it takes developers only 30 minutes to quickly set up a development environment. The Atlas 200 DK provides user-friendly GUIs and allows for all-scenario deployment after one-time development. Another highlight of the Atlas 200 DK is Tensor Boost Engine (TBE), an efficient operator development tool that features easy development and high performance. Pre-configured with various APIs, TBE simplifies development and supports the tuning of different custom operators. The in-depth software/hardware collaboration and optimization help TBE improve performance by 10%.

 The Huawei Atlas series covers scenarios across device-cloud-edge, providing the most demanding AI specifications.

Next, let’s talk about how to develop AI applications based on the Atlas 200. The process is simple. First, you need to download Mind Studio, which is an AI full-stack development platform based on the IntelliJ framework. It enables the development, debugging, and tuning of custom operators, and provides features such as network porting, optimization, and analysis, greatly simplifying application development. 

Thanks to diverse APIs, the Atlas 200 DK facilitates AI development for developers in an easy-to-use environment.

Talk is cheap, show me the code. The following C++ code is listed to illustrate the development process based on the Atlas 200 DK.

In addition to advanced technologies, Atlas also provides a developer-friendly platform. A critical part of this platform is the Ascend Developer Zone, a developer-centric enablement community built by Huawei.

In the Ascend Developer Zone, technical documents, development tools (such as the TBE operator development tool), and code samples (such as the manufacturing quality inspection model) are available for download under Resources. Theoretical courses, practical training, and application cases of AI are provided under Ascend Institute, and the support center provides convenient technical support in the form of online Q&A, remote support, and experience sharing, helping developers quickly get started.

We have ushered in a digital age where AI is increasingly pervasive and available. The all-digital world would be impossible without the innovation of developers across the globe. While Zeus sentenced Atlas for eternity, Huawei Atlas AI is a perfect gift to the developer community, and only a few clicks away. We call on all developers to share your collective wisdom and unleash your creativity.

To learn more about Atlas, please click here.