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Proliferation framework on input data set to improve memory latency in multicores for optimization

机译:输入数据集的扩散框架可改善多核中的内存延迟以进行优化

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In today's HPC world, numerous applications executed with high speed. The multi core architecture has provided a wide scope of exploration towards any kind of high-end applications. The paper gives an analogy on ability to handle the high-end input triggers by managing the core utilities at the lower end of the computer. The optimized way of memory block utilization, debugging proliferation and data management at configured input level discussed in the paper. The Data Proliferation framework model named as COMCO (Component for Compiler Optimization) model and it elaborates on how to handle configured inputs at the OS level. The paper gives an exploration of the configured inputs safely at the multi thread level using the COMCO (Component for Compiler Optimization) strategy.
机译:在当今的HPC世界中,许多应用程序都以高速执行。多核体系结构为各种高端应用提供了广泛的探索。本文通过管理计算机较低端的核心实用程序,提供了处理高端输入触发器的能力的类比。本文讨论了在配置的输入级别上优化内存块利用,调试扩散和数据管理的方法。名为COMCO(编译器优化的组件)模型的数据扩散框架模型,详细说明了如何在OS级别上处理已配置的输入。本文使用COMCO(编译器优化组件)策略在多线程级别安全地探讨了配置的输入。

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