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]。
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Data-intensive computing 数据密集型计算
data intensive computing architecture 计算密集型体系
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
The paper introduces the research trend for the access bottleneck between the data intensive computing architecture and memory.
文章介绍了计算密集型体系解决存储器访问瓶颈的研究趋势。
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。
While the storage computing in the grid is well suited for data-intensive storage, it is not economically suited for storing objects as small as 1 byte.
虽然网格中的存储计算非常适合数据密集型存储，但是存储一个字节大小的对象从经济上来说不合适。
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