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Hybrid Tree: A Scalable Optoelectronic Interconnection Network for Parallel Computing

机译：混合树：用于并行计算的可扩展光电互连网络

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E. John; F. Hudson; L. K. John;
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年度 1998
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1. The hybrid dynamic parallel scheduling algorithm for load balancing on Chained-Cubic Tree interconnection networks [J] . Basel A. Mahafzah, Bashira A. Jaradat The Journal of Supercomputing . 2010,第3期

机译：链立方树互连网络上用于负载均衡的混合动态并行调度算法
2. The hybrid dynamic parallel scheduling algorithm for load balancing on Chained-Cubic Tree interconnection networks [J] . Basel A. Mahafzah, Bashira A. Jaradat Journal of supercomputing . 2010,第3期

机译：链立方树互连网络上用于负载均衡的混合动态并行调度算法
3. A class of highly scalable optical crossbar-connected interconnection networks (SOCNs) for parallel computing systems [J] . Webb B., Louri A. IEEE Transactions on Parallel and Distributed Systems . 2000,第5期

机译：用于并行计算系统的一类高度可扩展的光交叉连接互连网络（SOCN）
4. Hybrid tree:a scalable optoelectronic interconnection network for parallel computing [C] . E.john, F.Hudson, L.K.John Hawaii international conference on system science;HICSS-31 . 1998

机译：混合树：用于并行计算的可扩展光电互连网络
5. A high-throughput, low-power asynchronous Mesh-of-Trees interconnection network for the eXplicit Multi-Threading (XMT) parallel architecture. [D] . Horak, Michael N. 2008

机译：一种用于吞吐量多线程（XMT）并行体系结构的高吞吐量，低功耗的异步树状互连网络。
6. Pyntacle: a parallel computing-enabled framework for large-scale network biology analysis [O] . Luca Parca, Mauro Truglio, Tommaso Biagini, 2020

机译：Pyntacle：用于大规模网络生物学分析的并行计算的支持框架
7. A Class of Highly Scalable Optical Crossbar-Connected Interconnection Networks (SOCNs) for Parallel Computing Systems [O] . Brian Webb, Ahmed Louri, Senior Member 2000

机译：一类用于并行计算系统的高度可扩展的光交叉连接互连网络（SOCN）
8. Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation. Appendix C. Fault Tolerant Interconnection Networks and Image Processing Applications for the PASM Parallel Processing Systems [R] . Adams, G. B. 1984

机译：信号处理的分布式计算：异步并行计算的建模。附录C. pasm并行处理系统的容错互连网络和图像处理应用

Hybrid Tree: A Scalable Optoelectronic Interconnection Network for Parallel Computing

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