高性能视距计算

Ligang Lu, B. Paulovicks, M. Perrone, V. Sheinin
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引用次数: 5

摘要

在本文中,我们介绍了我们最近在蜂窝宽带引擎(CBE)处理器上的多核视距计算的研究和开发工作。在需要实时高性能计算的许多应用程序中都可以找到LoS。我们将描述一种高效的LoS多核并行计算算法,包括数据分区和计算负载分配策略,以充分利用CBE的计算资源进行高效的LoS视图并行计算。此外,我们还将演示一种连续快速转置算法,为高效的单指令多数据(SIMD)操作准备输入数据。此外,我们还描述了数据输入和输出(I/O)管理方案,以减少直接内存访问(DMA)数据获取和存储操作中的(I/O)延迟。在超过419万个点的感兴趣区域(AOI)上对我们的LoS视图计算方案进行的性能评估表明,我们在CBE上的并行计算算法耗时不到25.5 ms,比可用的商业系统快了几个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High performance computing of line of sight viewshed
In this paper we present our recent research and development work for multicore computing of Line of Sight (LoS) on the Cell Broadband Engine (CBE) processors. LoS can be found in many applications where real-time high performance computing is required. We will describe an efficient LoS multi-core parallel computing algorithm, including the data partition and computation load allocation strategies to fully utilize the CBE's computational resources for efficient LoS viewshed parallel computing. In addition, we will also illustrate a successive fast transpose algorithm to prepare the input data for efficient Single-Instruction-Multiple-Data (SIMD) operations. Furthermore, we describe the data input and output (I/O) management scheme to reduce the (I/O) latency in Direct-Memory-Access (DMA) data fetching and storing operations. The performance evaluation of our LoS viewshed computing scheme over an area of interest (AOI) with more than 4.19 million points has shown that our parallel computing algorithm on CBE takes less than 25.5 ms, which is several orders of magnitude faster than the available commercial systems.
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