Facebook gives system design for deep learning servers free

Dec

12

2015

Facebook made the technology of his Big Sur servers public. The systems are optimized for deep learning calculations allow computers to recognize speech and image.

Big Sur is compatible with the Open Rack V2 standard from the Open Compute Project. This project was set up by Facebook to make full documentation on data center systems, public and also the design and specifications of Big Sur are distributed through Open Compute. The specific details of the system have yet to be made public.

Facebook has Big Sur along with Nvidia developed standard system contains eight M40 Tesla cards. According to the company Big Sur but also be equipped with other PCI-e cards. Despite the considerable amount of GPU computing server would not need special cooling. The design is built for easy access to hardware components in mind. This allows components to be replaced regularly as hard drives and memory DIMM, quick changeover.

Facebook Big Sur
Facebook Big Sur
Facebook Big Sur

The motherboard can be replaced according to the social network in a minute, where it would take an hour previous comparable servers. It would also replace all toolless can happen; only for swapping the CPU cooler is a screwdriver. With green indicates where mechanics can touch these parts.

According to Facebook’s Big Sur twice as fast as the previous generation systems that used the company for deep learning. Machine learning and artificial intelligence are becoming increasingly important for tech giants like Facebook, Google, Microsoft and IBM.

The techniques enable companies to build services around ‘understanding’ of large complex datasets. For exemple recognizing voices and images, choosing content for news feeds, personal assistants and translating content on the techniques. By making public the technology, the companies hope the innovation to give a push in the back, where they themselves can benefit. So did Google have self-learning software TensorFlow early November opensource.

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