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Distributed net-centric architecture of m2m acquisition units with Optical GVA

机译:具有光学GVA的m2m采集单元的分布式以网络为中心的架构

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This paper describes the architecture of a low-latency symmetric multiprocessing optical soft memory system to cluster computing inside the core of an adaptive optical signal processor with the aid of soft decision algebraic polynomial algorithms. The optical system hardware is shown to evolve along with the iterator instantiations of the soft algorithm that forms the core of the memory map. The system enables efficient cache coherence protocols used in unit multiprocessors to be run across a homogeneous cluster in optical soft memory systems. We define a structure called the Optical Generalized Viterbi Algorithm Data Structure (Optical GVA DS) that makes up the system map for adaptive optical signal processing. The system executes transforms where algorithms for handling the entire data vector is processed, shortening the computational complexity effectively. Thus the optical soft memory system as described by the evolving Optical GVA DS iterator instantiates enables the design of parallel processors to handle modulated data in the optical domain. This is of importance in the realization of distributed net-centric architectures and forms the basis of large-scale real-time data processing and acquisition in m2m units.
机译:本文介绍了一种低延迟对称多处理光学软存储系统的体系结构,以借助软判决代数多项式算法在自适应光学信号处理器的内核内部进行聚类计算。示出了光学系统硬件与形成存储器映射图核心的软算法的迭代器实例一起发展。该系统使在单元多处理器中使用的高效缓存一致性协议能够在光学软存储系统中的同质集群上运行。我们定义了一种称为光学通用维特比算法数据结构(Optical GVA DS)的结构,该结构构成了自适应光信号处理的系统图。该系统执行转换,其中处理用于处理整个数据向量的算法,从而有效地缩短了计算复杂度。因此,由演进的光学GVA DS迭代器实例化描述的光学软存储系统使并行处理器的设计能够处理光域中的调制数据。这对于以分布式网络为中心的体系结构的实现很重要,并构成了以m2m为单位的大规模实时数据处理和采集的基础。

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