OODA Workflow OODA: Observation,Orientation,Decision,Action Deep Learning Platform Tools
The goal of this project is to build and apply open source platforms for deep learning applications.
Develop algorithm library and sample library for artificial intelligence application software, integrate two kinds of applications (biological image big data analysis, genetic data analysis), and demonstrate on sugon advanced computing platform.
Complete the function development of algorithm library and sample library. The machine learning algorithm is developed to accelerate the core library, which is deployed and integrated into sugon advanced computing service platform. Based on the home-made hugon processor, the library is available for users to call. The accelerated core library will be closely coupled to the optimization of high-performance computer system at all levels.
Implement the algorithm tool set that supports the efficient parallel execution of large-scale machine learning and partially open source. The algorithm tool set should be integrated into sugon advanced computing platform to provide application services.
Responsible for the transplantation and integration of more than two kinds of applications (big data analysis of biological image and gene data analysis) into sugon advanced computing service platform, completing the support of typical application process, and reaching the leading level in terms of performance and scalability.
A performance tuning and knowledge management suit #Introduction PAK is a general scientific application autotuning framework which can significantly decrease the work of the programmer and improve the speed of optimising code. We believe optimising code must be an enjoyable, creative experience. PAK attempts to take the pain out of programmers by taking different models used in processes of optimising projects, such as extracter feature model, optimiser model. PAK is accessible, yet powerful, providing powerful tools needed for large, robust applications.