基于多块结构网格大规模并行计算的负载均衡设计及实现

结构网格具有网格生成速度快、质量高、数据结构相对简单、较适用于流体表面应力集中的运算等优点。在大规模 CFD（Computational Fluid Dynamics）并行计算中,需要将网格区域划分为多块网格,而多块网格之间的数据通信会制约并行计算能力的提高,因此对结构网格的负载平衡优化是提高并行计算能力的重点。本文提出了一个采用多层次 k-way 多约束条件图剖分算法来改进负载平衡的方案,并对 M6 翼型和 CRM 模型的多种规模进行了实际计算,结果证明多层次 k-way图剖分算法能够有效地优化负载平衡,在此基础上得到了最优节点间的计算负载平衡和通信负载平衡,最终达到了理想的并行效率。     

支持过程级动态软硬件划分的RSoC设计与实现

目前,可重构计算平台所支持的动态软硬件划分粒度多处于线程级或指令级,但线程级划分开销太大,而指令级划分又过于复杂,因此很难被用于实际应用之中。本文设计并实现了一种支持过程级动态软硬件划分的可重构片上系统(RSoC),提出了一种过程级硬件透明编程模型,给出了过程级的硬件封装方案;在分析软硬件过程根本区别的基础上,针对硬件过程开发了专门的管理模块,并利用部分动态重构等技术,实现了硬件过程的动态配置。实验表明该系统能够较好的支持过程级的动态软硬件划分,实现了节省资源、简化设计,提高性能等目的。     

Efficient embedded wavelet codec based on list structure

A new efficient image codec called embedded wavelet coding based on list structure (EWCBL) is proposed in this paper. By combining the techniques of morphological representation and quadtree partitioning, EWCBL effectively exploits both within-subband clustering and cross-subband similarity of wavelet coefficients. Based on the list structure, a fine fractional bit-plane coding is employed to achieve excellent rate-distortion performance. The patterned morphological dilation is introduced to greatly reduce the redundant test operations. Experimental results show that the proposed EWCBL outperforms state-of-the-art embedded codecs for both lossy and lossless compression. Moreover, the good performance and features of embeddedness and scalability are achieved with relatively low complexity.     

One-dimensional partitioning for heterogeneous systems: Theory and practice

We study the problem of one-dimensional partitioning of nonuniform workload arrays, with optimal load balancing for heterogeneous systems. We look at two cases: chain-on-chain partitioning, where the order of the processors is specified, and chain partitioning, where processor permutation is allowed. We present polynomial time algorithms to solve the chain-on-chain partitioning problem optimally, while we prove that the chain partitioning problem is NP-complete. Our empirical studies show that our proposed exact algorithms produce substantially better results than heuristics, while solution times remain comparable.     

An architecture framework for an adaptive extensible processor

To improve the performance of embedded processors, an effective technique is collapsing critical computation subgraphs as application-specific instruction set extensions and executing them on custom functional units. The problem with this approach is the immense cost and the long times required to design a new processor for each application. As a solution to this issue, we propose an adaptive extensible processor in which custom instructions (CIs) are generated and added after chip-fabrication. To support this feature, custom functional units are replaced by a reconfigurable matrix of functional units (FUs). A systematic quantitative approach is used for determining the appropriate structure of the reconfigurable functional unit (RFU). We also introduce an integrated framework for generating mappable CIs on the RFU. Using this architecture, performance is improved by up to 1.33, with an average improvement of 1.16, compared to a 4-issue in-order RISC processor. By partitioning the configuration memory, detecting similar/subset CIs and merging small CIs, the size of the configuration memory is reduced by 40%.     

A new graph cut-based multiple active contour algorithm without initial contours and seed points

This paper presents a new graph cut-based multiple active contour algorithm to detect optimal boundaries and regions in images without initial contours and seed points. The task of multiple active contours is framed as a partitioning problem by assuming that image data are generated from a finite mixture model with unknown number of components. Then, the partitioning problem is solved within a divisive graph cut framework where multi-way minimum cuts for multiple contours are efficiently computed in a top-down way through a swap move of binary labels. A split move is integrated into the swap move within that framework to estimate the model parameters associated with regions without the use of initial contours and seed points. The number of regions is also estimated as a part of the algorithm. Experimental results of boundary and region detection of natural images are presented and analyzed with precision and recall measures to demonstrate the effectiveness of the proposed algorithm.     

网格资源超图划分聚类任务调度

网格计算是当前一个活跃的研究领域,其中任务调度是实现网格计算目标的一个重要部分.为获得良好的网格任务调度性能,提出了一种基于资源超图划分聚类的网格任务调度算法RHPC.该算法根据网格环境下资源数量庞大、异构、多样的特点,在构建的网格资源超图模型基础上,预先对资源进行性能划分聚类,将任务与聚类资源相匹配并实施调度.模拟实验结果证明算法缩短了任务资源相匹配的时间,提高了任务调度的性能,是一种有效的网格任务调度算法.     

一种基于信道状态的H．264的数据不平等保护策略

根据H．264标准的数据分类功能,提出一种数据的不平等保护策略。该策略利用信道的反馈信息预测信道丢包率,调整H．264视频码流各分类区的信道码率。实验结果表明,该策略能有效的提高视频码流的误码鲁棒性。     

一种基于信道状态的H.264的数据不平等保护策略

根据H.264标准的数据分类功能,提出一种数据的不平等保护策略。该策略利用信道的反馈信息预测信道丢包率,调整H.264视频码流各分类区的信道码率。实验结果表明,该策略能有效的提高视频码流的误码鲁棒性。