Huawei Launches AI Ecosystem Program in Europe

100M Euros Investment in 5 Years

4,401

Huawei has officially released the AI Ecosystem Program in Europe and announced an investment of 100 million euros in the next 5 years. This program unlocks a new chapter for the computing industry in Europe.

According to Jiang Tao, VP of Intelligent Computing BU,

“Huawei is committed to investing in the AI computing industry in Europe, enabling enterprises and individual developers to leverage the Ascend AI series products for technological and business innovation. Over the next 5 years, Huawei plans to invest 100 million euros in the AI Ecosystem Program in Europe, helping industry organisations, 200,000 developers, 500 ISV partners, and 50 universities and research institutes to boost innovation.”

The 4 initiatives of the program are as follows:

First, Huawei will work with partners to shape the AI industry in Europe. Specifically, Huawei will collaborate with key organizations in three important areas:

  • Improve regulations and standards on AI ethics and security together with the European AI Alliance and European Telecommunications Standards Institute (ETSI)
  • Work with the Big Data Value Association (BDVA) to promote the AI Public-Private Partnership (PPP) across the EU, helping boost AI research and vertical industry development
  • Nurture the AI university ecosystem in Europe through academic platforms, like the Falling Walls Foundation

Second, Huawei will develop joint solutions with ISV partners. The OpenLabs in Munich and Paris are AI capability centers that support ISV partners in hardware, development and porting, and joint marketing.

Third, based on the Ascend Developer Community, Huawei will organize offline technological salons and developer contests, and provide technological support to enable developers.

Fourth, Huawei will provide partners with AI courses and teaching materials, and establish joint labs in Europe. 3 AI courses designed for universities will cover basic AI theory, Ascend and mainstream framework development, and Ascend software architecture and development guides. 4 teaching materials on Ascend development will be released in 2020. In addition, Huawei will establish joint labs with partner universities and research institutes for algorithm model development and basic applications.

The Full Atlas Product Lineup Unleashes Ultimate Computing Power for Training

At HUAWEI CONNECT 2019 (Shanghai), Huawei launched a broad product portfolio based on the Ascend 910, the industry’s most powerful AI training processor. The products include the Atlas 300 AI training card, Atlas 800 training server, and Atlas 900 AI training cluster. The Atlas series products support all scenarios across device-edge-cloud, accelerating intelligent transformation of industries with ultimate computing power for training.

The Atlas 300 training card provides computing power up to 256 TFLOPS, doubling that of the industry’s mainstream training cards. With Atlas 300, the number of images trained per second soars from 965 to 1,802. The Atlas 300 supports direct 100G RoCE interfaces for parallel transmission of gradient parameters and datasets, reducing the gradient synchronization latency by up to 70% and slashing the cluster training time to seconds.

The Atlas 800 AI training server integrates 8 Ascend 910 AI processors in a 4U space. It provides computing power up to 2 PFLOPS, with computing power density 2.5x that of industry counterparts. The Atlas 800 weighs only 75 kg, which is less than half of the industry average. It has 32 built-in hardware decoders that decode 16,384 1,080p images per second, outperforming the processing capability of mainstream products by 25x. Besides, the Atlas 800 enables parallel processing of image decoding and training. The Atlas 800 supports air and liquid cooling, meeting requirements of enterprise data centers and high-density cluster deployment. The energy efficiency of a single Atlas 800 server is 1.8 times that of peer products.

The Atlas 900 AI training cluster contains 1,024 Ascend 910 AI processors. The ResNet-50 image classification model is the most authoritative standard measuring AI computing power. It takes Atlas 900 just 59.8s to train a ResNet-50 model in the test. With the same precision, the Atlas 900 breaks the previous world record by 10 seconds for being the world’s fastest AI training cluster. The powerful computing of Atlas 900 makes a difference in scientific research and business innovation, such as astronomical exploration, weather forecasting, autonomous driving, and oil exploration.

Rapid Mobile uses cookies, tokens, and other third party scripts to recognise visitors of our sites and services, remember your settings and privacy choices, and - depending on your settings and privacy choices - enable us and some key partners to collect information about you so that we can improve our services and deliver relevant ads.

 

By continuing to use our site or clicking Agree, you agree that Rapid Mobile and our key partners may collect data and use cookies for personalised ads and other purposes, as described more fully in our privacy policy.

 

You can change your settings at any time by clicking Manage Settings or by visiting our Privacy Centre for more detailed information.

 

Privacy Settings saved!
Cookie Services

When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. Click on the different category headings to find out more and change our default settings. However, blocking some types of cookies may impact your experience of the site and the services we are able to offer.

These cookies are necessary for the website to function and enable essential services and functonality, including identify verification, service continuity and site security. Opt out is not availabe.

Essential Session management cookies for logged in users
  • wordpress_test_cookie
  • wordpress_logged_in_
  • wordpress_sec

For perfomance reasons we use Cloudflare as a CDN network. This saves a cookie "__cfduid" to apply security settings on a per-client basis. This cookie is strictly necessary for Cloudflare's security features and cannot be turned off.
  • __cfduid

Used by Spamshield to stop spam signups
  • _wpss_h_
  • _wpss_p_

NewsWire Service
  • BIGipServerwidget2_www_http

Decline all Services
Accept all Services