Study of SSIN (Single Stage Interconnection Networks) Parallel Processing Interconnection Networks

1988 ◽  
Author(s):  
Dharma P. Agrawal
2015 ◽  
Vol 26 (01) ◽  
pp. 159-168 ◽  
Author(s):  
Xianyong Li ◽  
Xiaofan Yang ◽  
Li He ◽  
Cui Yu ◽  
Jing Zhang

Fault tolerance is especially important for interconnection networks, vastly influencing the performance of the parallel processing systems underlying the corresponding networks. This paper studies the fault tolerance of radix-k n-dimensional hypermesh optical interconnection networks, determines the connectivity of partial hypermesh, and derives the conditional connectivity of hypermesh provided that each adjacent set cannot be faulty simultaneously. Under this condition, the hypermesh networks can tolerate up to 2n(k-1)-k-1 fault processors without being disrupted, implying that when the number of dimension n (respectively, radix-k) is a fixed value in the hypermesh network, the larger the value of radix-k (respectively, dimension n) is, the higher the reliability and availability of the network becomes.


Mathematics ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 1214 ◽  
Author(s):  
Zhipeng Xu ◽  
Xiaolong Huang ◽  
Fabian Jimenez ◽  
Yuefan Deng

Using three supercomputers, we broke a record set in 2011, in the enumeration of non-isomorphic regular graphs by expanding the sequence of A006820 in the Online Encyclopedia of Integer Sequences (OEIS), to achieve the number for 4-regular graphs of order 23 as 429,668,180,677,439, while discovering several regular graphs with minimum average shortest path lengths (ASPL) that can be used as interconnection networks for parallel computers. The enumeration of 4-regular graphs and the discovery of minimal-ASPL graphs are extremely time consuming. We accomplish them by adapting GENREG, a classical regular graph generator, to three supercomputers with thousands of processor cores.


2015 ◽  
Vol 15 (01n02) ◽  
pp. 1550006
Author(s):  
WENJUN XIAO ◽  
WEIDONG CHEN ◽  
BEHROOZ PARHAMI

The hypercubic family of interconnection networks, encompassing the hypercube and its derivatives and variants, has a wide range of applications in parallel processing. Various problems in general complex networks can be addressed by choosing a hypercubic network as a skeleton. In this paper, we provide insight into why hypercubic networks are suitable as network skeletons and discuss a mapping scheme to take advantage of the symmetry of such networks for developing efficient algorithms.


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