在由多计算机机群构成的网格环境下，为了实现数据并行型计算，提出了一个基于多智能体机制的网格开发模型。
For implementing the data parallel computing (DPC) in grid that composed of multi-clusters, a grid development model based on multiagent is discussed.
支持Dryad(大伸缩量，数据密集型的并行计算)(即将提供)。
Support for Dryad (large scale, data-intensive parallel programming) (soon).
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。
Abstract CUDA is a parallel computing architecture introduced by NVIDIA, it mainly used for large scale data-intensive computing.
与CPU相比，GPU专为高度并行化和密集型的计算而设计，它能使更多的晶体管用于数据处理，而非数据缓存或流控制。
Compared with CPU, GPU was designed for compute-intensive, highly parallel computing, which enabled more transistors to be used for data processing, rather than data caching or flow control.
与CPU相比，GPU专为高度并行化和密集型的计算而设计，它能使更多的晶体管用于数据处理，而非数据缓存或流控制。
Compared with CPU, GPU was designed for compute-intensive, highly parallel computing, which enabled more transistors to be used for data processing, rather than data caching or flow control.
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