共查询到20条相似文献,搜索用时 78 毫秒
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简要介绍了目前PROFIBUS规范的发展现状,给出了PROFIBUS-DP现场应用存在中的问题,分析了产生该问题的原因,并向读者提供了解决该问题的方法,其对PROFIBUS-DP研发具有极强的参考价值和指导意义。 相似文献
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本文从理论上系统的研究了循环冗余校验(CRC)码的原理和性质,解决了在实际应用中经常碰到的如何设置寄存器的初始值及如何选取生成多项式的问题;同时,通过分析不同长度下算法的性能差异提出了CRC算法对校验数据的长度没有限制的观点。最后,提出了CRC逆运算的概念。 相似文献
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任意长度信息序列的CRC快速算法 总被引:2,自引:0,他引:2
CRC(循环冗余校验码)编码是数字信号传输中用得较普遍的一种差错控制编码。它不但可以用于纠正独立的随机错误,也可以用于纠正突发错误。CRC校验通常是靠专用硬件电路来实现的,但很多系统为了降低成本,常常利用单片机或微处理器编程来完成这一功能。因此,在器件处理能力有限的情况下,如何提高CRC校验软件计算的速度,是开发者最为关心的问题。 相似文献
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随着图像数据的大量增加,传统单处理器或多处理器结构的计算设备已无法满足实时性数据处理要求。异构并行计算技术因其高效的计算效率和并行的实时性数据处理能力,正得到广泛关注和应用。利用GPU在图形图像处理方面并行性的优势,提出了基于OpenCL的JPEG压缩算法并行化设计方法。将JPEG算法功能分解为多个内核程序,内核之间通过事件信息传递进行顺序控制,并在GPU+CPU的异构平台上完成了并行算法的仿真验证。实验结果表明,与CPU串行处理方式相比,本文提出的并行化算法在保持相同图像质量情况下有效提高了算法的执行效率,大幅降低了算法的执行时间,并且随着图形尺寸的增加,算法效率获得明显的提升。 相似文献
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针对尺度不变特征变换(SIFT)算法实时性差的问题,提出了利用开放式计算语言(OpenCL)并行优化的SIFT算法。首先,通过对原算法各步骤进行组合拆分、重构特征点在内存中的数据索引等方式对原算法进行并行化重构,使得算法的中间计算结果能够完全在显存中完成交互;然后,采用复用全局内存对象、共享局部内存、优化内存读取等策略对原算法各步骤进行并行设计,提高数据读取效率,降低传输延时;最后,利用OpenCL语言在图形处理单元(GPU)上实现了SIFT算法的细粒度并行加速,并在中央处理器(CPU)上完成了移植。与原SIFT算法配准效果相近时,并行化的算法在GPU和CPU平台上特征提取速度分别提升了10.51~19.33和2.34~4.74倍。实验结果表明,利用OpenCL并行加速的SIFT算法能够有效提高图像配准的实时性,并能克服统一计算设备架构(CUDA)因移植困难而不能充分利用异构系统中多种计算核心的缺点。 相似文献
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Song Kai Li Wen Zhang Boyang Yan Liping Wang Xianchao 《The Journal of supercomputing》2022,78(13):14965-14990
The Journal of Supercomputing - The Jacobi iterative algorithm has the characteristic of low computational load, and multiple components of the solution can be solved independently. This paper... 相似文献
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Theoretical aspects of encoding cyclic redundant codes (CRCs) are reviewed. A method of designing hardware parallel encoders for CRCs that is based on digital system theory and z -transforms is presented. It allows designers to derive the logic equations of the parallel encoder circuit for any generator polynomial. A few interesting application areas for hardware parallel encoders are pointed out 相似文献
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Peter J. Varman Balakrishna R. Iyer Donald J. Haderle Stephen M. Dunn 《Parallel Computing》1990,15(1-3):165-177
An efficient parallel algorithm for merging two sorted lists is presented. The algorithm is based on a novel partitioning algorithm that splits the two lists among the processors, in a way that ensures load balance during the merge. The partitioning algorithm can itself be efficiently parallelized, allowing the solution to scale with increased numbers of processors. A shared memory multiprocessor is assumed. The time complexity for partitioning and merging is O(N/p + log N), where p is the number of processors and N is the total number of elements in the two lists. Implementation results on a twenty node Sequent Symmetry multiprocessor are also presented. 相似文献
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Genetic Parallel Programming: design and implementation 总被引:1,自引:0,他引:1
This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially. 相似文献