It is worth noting that Inspur, a re-elected OSSC member, was also re-elected as the chair of the SPEC Machine Learning (SPEC ML) working group. The development plan of ML test benchmark proposed by Inspur has been approved by members which aims to provide users with standard on evaluating machine learning computing performance. SPEC is a global and authoritative third-party application performance testing organization established in 1988, which aims to establish and maintain a series of performance, function, and energy consumption benchmarks, and provides important reference standards for users to evaluate the performance and energy efficiency of computing systems. The organization consists of 138 well-known technology companies, universities and research institutions in the industry such as Intel, Oracle, NVIDIA, Apple, Microsoft, Inspur, Berkeley, Lawrence Berkeley National Laboratory, etc., and its test standard has become an important indicator for many users to evaluate overall computing performance. The OSSC executive committee is the permanent body of the SPEC OSG (short for Open System Group, the earliest and largest committee established by SPEC) and is responsible for supervising and reviewing the daily work of major technical groups of OSG, major issues, additions and deletions of members, development direction of research and decision of testing standards, etc. Meanwhile, OSSC executive committee uniformly manages the development and maintenance of SPEC CPU, SPEC Power, SPEC Java, SPEC Virt and other benchmarks.

Inspur, a leading data center and AI full-stack solutions provider, today announced two AI-technology driven open computing systems. The X-MAN 4.0, developed with Baidu, is the world's first OAI (Open Accelerator Infrastructure) compliant and liquid cooling rack-scale AI computing product optimized specifically for deep neural network applications. The Inspur OAI UBB system, meanwhile, is a 21-inch Full-Rack OAM solution delivering efficiency, flexibility and management. Workloads in data centers are growing more diverse and complex with artificial intelligence and other emerging technologies and applications spreading rapidly. Plus, Internet companies are struggling with AI's increasing hardware complexity--integrating an AI accelerator typically takes 6 to 12 months.

If you want to see what the future of iron to support machine learning looks like, then perhaps the best place to look at what the hyperscalers and cloud builders who account for the vast majority of processing and applications in this field are deploying. Or, more precisely, look at the iron that their ODM partners are trying to peddle to other companies that is inspired by what the hyperscalers and cloud builders are using. Inspur, one of the upstart makers of infrastructure that is located in China but which is expanding outwards to North America and Europe, is a good case in point. The company has very good insight into what the Big Four in China – Alibaba, Baidu, Tencent, and either China Mobile or JD.com, depending on how you want to rank numbers four and five – are doing with their vast infrastructure, and it dominates some of these accounts. As we reported back in October 2018, when Inspur was making a push into Open Compute, Inspur has about half of the plain vanilla server shipments and about 80 percent of the GPU accelerated machine learning shipments to the hyperscalers and cloud builders in China. Inspur also works with Microsoft, one of the Big Four in the United States, on its current generation "Project Olympus" servers, the designs of which have been open sourced through the Open Compute Project championed by Facebook alongside some other hyperscale iron that was inspired by Inspur's manufacturing deals with Alibaba and Tencent.

China-based Inspur rolled out a new set of Open Compute Project (OCP)-based hyperscale rack servers that included support for artificial intelligence. Inspur is the third-largest server vendor in the world and the biggest in China, according to Dolly Wu, vice president of data center and cloud at Inspur. Inspur's technology has cornered 57% of the artificial intelligence (AI) market share in China, and now it has included some of that technology into one of its new server nodes. "The highlight that we want to bring for the OCP community is that Inspur is introducing several new compute modules using the San Jose motherboard, which we contributed to OCP last year," Wu said in an interview with FierceTelecom. Using this motherboard, we've created three new compute modules."

As the pioneer in artificial intelligence field, Baidu chose the Inspur NF5568M4 heterogeneous supercomputing server in its unmanned auto road condition model training. Artificial intelligence has advanced through the years and voice recognition, intelligent hardware, and driverless cars are all technologies that influence our lives. Behind artificial intelligence technology is a neural network that is built from deep learning -- mimicking mechanisms of the human brain when interpreting data. In order to meet all the latest deep learning requirements, a high-performance CPU GPU co-processing acceleration server is growing to become the essential foundation for artificial intelligence hardware.

The 4U4 card design of Inspur NF5568M4 is applicable to present electric power and heat dissipation designs of the data center, and is scalable to multi-machine and multi-card CPU computing clusters via the open-source Inspur Caffe-MPI becoming the mainstream CPU server used presently in the internet industry. Currently, Inspur's deep learning solution is being applied at Tencent, Baidu, Alibaba, Qihoo, iFLYTEK and JD and is supporting the "super brains" of various types of intelligentized services. As the neural network model grows in complexity, the computing performance necessary for the model training increases dramatically. The cluster-edition Caffe-MPI computing frame launched by Inspur achieves parallel computing of GPU server. It adopts high-performance mature MPI technology in computing -- carrying out parallel data optimization to the Caffe edition -- with the ability to organize multiple NF5568M4 into CPU parallel computing clusters via IB network.