数据密集型计算(Data Intensive Computing)是采用数据并行方法实现大数量并行计算的应用,计算数据量级为TB或PB级,因此也被成为是大数据的核心支撑技术[1]。
基于74个网页-相关网页
Data-intensive computing 数据密集型计算
Data Intensive Computing at KTH 数据集中计算
Data Intensive Super Computing 数据密集型的超级计算
Data-Intensive Parallel Computing 数据密集型并行计算
Considering most GIS buffer analysis is data intensive computing, the task was decomposed according to the map layer and geographic spatial area.
考虑到大多数地理信息系统中缓冲区分析数据的特点,提出了基于图层和地理空间区域的任务分解方法。
Abstract CUDA is a parallel computing architecture introduced by NVIDIA, it mainly used for large scale data-intensive computing.
摘要CUDA是一种由NVIDIA推出的并行计算架构,非常适合大规模数据密集型计算。
Data Grid is widely used in data-intensive computing, which provide rapid information retrieval and data access support for large amounts of distributed storage data resources.
数据网格广泛应用于数据密集型计算,为大数据量、分布存储数据资源提供快速的信息检索和数据访问的支持。
应用推荐