A construction layout about flexible, convent, new type, multi parameter, high accuracy, large volume data acquisition system for the Rubidium atomic frequency standard test is put forward.
For the communication between large volume data acquisition system and computers, a hierarchical communication mode is put forward. The h/w configuration & s/w design of the data acquisition system are introduced.
2. The microcomputer-based greenhouse monitoring & controlling system has been developed around an ATMEL microcontroller which is reinforce by multiplex A/D sampling module; large volume data on-line storage module ; real-time clock module ;
Some key techniques used in the system development process are introduced, such as the mapping between object model and database model, the authorization model based on RBAC (Role Based Access Control) and the usage of stored procedure for large volume data search to improve performance.
本文总结了在系统开发过程中使用的一些关键技术点,包括:对象模型与数据库模型的映射、基于RBAC(Role Based Access Control)的权限模型、使用查询分页存储过程解决大数据量的性能问题等。
It also uses BEA's TUXEDO transaction middleware and associated database partition technology to conduct the data input parallel processing and load balance, and resolve the processing bottleneck problem of large volume data input and the problem of smooth expansion of hardware and software.
In information society nowadays, how to integrate these separate, self-governed OLTPs , to develop the effective methods to manage the large volume data, to mine the potential of information using data resource, to improve the ability and efficiency, todecrease the management cost, of Press and Publication management, become the great challenge and problems.
A collaborative and parallel visualization model is presented. The system structure, which consists of five levels, is hardware independent and portable. A cache coherent Distributed Shared Volume Buffer (DSVB) manages distributed storage of large volume data, and provides an uniform access to it. With the Distributed Visualization Application Interface (DVAI), the parallel visualization programming is transparent to high level applications. The Human Human User Interface is designed to support the cooperative...
A collaborative and parallel visualization model is presented. The system structure, which consists of five levels, is hardware independent and portable. A cache coherent Distributed Shared Volume Buffer (DSVB) manages distributed storage of large volume data, and provides an uniform access to it. With the Distributed Visualization Application Interface (DVAI), the parallel visualization programming is transparent to high level applications. The Human Human User Interface is designed to support the cooperative work, and provides more natural way of Human Human communication.
Small volume data can be directly rendered with texture mapping hardware in real time. However, limited texture memory prevents the method from being used to render large volume data efficiently. In this paper, A new approach was proposed to accelerate volume rendering with texture mapping hardware. Based on a new volume loading pipeline, the volume data was preprocessed efficiently before rendering. Only the volume data that contain object voxels are loaded into...
Small volume data can be directly rendered with texture mapping hardware in real time. However, limited texture memory prevents the method from being used to render large volume data efficiently. In this paper, A new approach was proposed to accelerate volume rendering with texture mapping hardware. Based on a new volume loading pipeline, the volume data was preprocessed efficiently before rendering. Only the volume data that contain object voxels are loaded into texture memory and resampled for rendering. Test shows that about 40% to 60% of the rendering time is saved by our method for large volume data.
For the communication between large volume data acquisition system and computers, a hierarchical communication mode is put forward. The h/w configuration & s/w design of the data acquisition system are introduced. This system has been put into operation with good result. Through simple method, the number of collection point can be expanded to 130,000.
large volume data
大规模体数据
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