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The SDAV Software Frameworks for Visualization and Analysis on Next-Generation Multi-Core and Many-Core Architectures

机译:用于下一代多核和多核架构的可视化和分析的SDAV软件框架

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This paper surveys the four software frameworks being developed as part of the visualization pillar of the SDAV (Scalable Data Management, Analysis, and Visualization) Institute, one of the SciDAC (Scientific Discovery through Advanced Computing) Institutes established by the ASCR (Advanced Scientific Computing Research) Program of the U.S. Department of Energy. These frameworks include EAVL (Extreme-scale Analysis and Visualization Library), DAX (Data Analysis at Extreme), DIY (Do It Yourself), and PISTON. The objective of these frameworks is to facilitate the adaptation of visualization and analysis algorithms to take advantage of the available parallelism in emerging multi-core and many-core hardware architectures, in anticipation of the need for such algorithms to be run in-situ with LCF (leadership-class facilities) simulation codes on supercomputers.
机译:本文调查了作为SDAV(可伸缩数据管理,分析和可视化)研究所(由ASCR(高级科学计算)建立的SciDAC(通过高级计算进行科学发现)研究所之一)的可视化支柱的一部分而开发的四个软件框架。研究)美国能源部计划。这些框架包括EAVL(极限分析和可视化库),DAX(极限数据分析),DIY(自己动手)和PISTON。这些框架的目的是促进对可视化和分析算法的适应,以利用新兴的多核和多核硬件体系结构中的可用并行性,因为预计此类算法需要与LCF一起现场运行(领导级设施)超级计算机上的模拟代码。

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