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Parallel shear-warp factorization on THPCS

机译:PRPC的平行剪切术分解

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摘要

Several approaches have been proposed to visualize 3D volume data on multiprocessor systems in recent years. Most of these algorithms are tailored for special architectures and hard to immigrate to new architectures, such as the Tsinghua High-Performance Cluster System (THPCS). In this paper, a parallel volume rendering algorithm is presented for THPCS. To reduce the communication cost and the complexity of blending local intermediate images, a static subtask distribution strategy is proposed. Combined with a prediction for the subtask load and node performance, our strategy yields a perfect load balance. An asynchronous binary compositing method is adopted to provide flexibility for our algorithm. The experimental results demonstrate the efficiency and practicality of our algorithm. As a result, THPCS using our algorithm achieves performance of rendering 512/sup 2/ color images for 128/sup 2//spl times/197 volume within 1 second.
机译:已经提出了几种方法来近年来在多处理器系统上可视化3D卷数据。这些算法中的大多数是针对特殊架构而定制的,并且难以移植到新的架构,例如清华高性能集群系统(THPC)。本文提出了一种平行体积呈现算法进行THPC。为了降低通信成本和混合本地中间图像的复杂性,提出了一种静态子任务分布策略。结合对子任务负荷和节点性能的预测,我们的策略产生了完美的负载平衡。采用异步二进制合成方法为我们的算法提供灵活性。实验结果表明了我们算法的效率和实用性。因此,使用我们的算法的THPC可以实现渲染512 / sup 2 /彩色图像的性能,以便在1秒内为128 / sup 2 // spl时间/ 197体积进行。

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