SALT LAKE CITY, Nov. 17, 2016 /PRNewswire/ -- Inspur released a report at the 2016 Global Supercomputing Conference (SC16) sharing the latest developments and applications of the KEEP program. The KEEP program (Knights Landing Evaluation and Escalation Program) is a pilot program jointly launched this past June by Inspur and Intel - based on Intel's new generation many-core processor, Knights Landing (KNL). In the KEEP program, Inspur and Intel jointly established an open and high-performance computing system based on brand-new KNL technology. During the first stage, a KNL testing system with a calculation capacity of over 200 TFlops was built - expandable to 700 TFlops later to help more high-performance computing and deep-learning users to accomplish application tests, transfers and optimization for the KNL. As presented at the conference, many users from different fields are deeply involved in the KEEP program - from traditional high-performance computing areas, such as oceanographic simulation, fluid mechanics computing, astronomical data processing and oil exploration, to new emerging fields such as HPDA - a combination of high-performance computing, big data, and intelligent computing, etc. Several KEEP program user experiences show that KNL is not only the most powerful many-core computer processor, it is also programming-friendly. Additionally, the basic performance reaches at least twice that of a dual-socket E5-2680 v4 CPU even without code level deep optimization. There is even more room to improve the performance when code-level deep optimization is performed specifically for the structural characteristics, or for the application algorithms of the KNL. KNL will continue to greatly improve the application of high-performance computing, deep learning, intelligent computing and big data applications, and a growing number of future applications will apply KNL to achieve better performance. The large number of realistic and reliable HPC application optimization experiences gathered via the KEEP program will undoubtedly contribute to the acceleration of the broader application and popularization of KNL.