The Hyperstar Interconnection Network

Al-Ayyoub, Abdel Elah; Day, Khaled

doi:10.1006/jpdc.1997.1414

Cited by 22 publications

(20 citation statements)

References 40 publications

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“…The major drawback of the Star network is related to its scalability problem [21]. The size of the Star network increases as a factorial function, and thus grows widely very rapidly; for example, the value of 5!…”

Section: Definitions and Topological Propertiesmentioning

confidence: 99%

Efficient Load Balancing Algorithm for the Arrangement-Star Network

Awwad¹,

Al-Sadi²

2016

ijacsa

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Abstract-The Arrangement-Star is a well-known network in the literature and it is one of the promising interconnection networks in the area of super computing, it is expected to be one of the attractive alternatives in the future for High Speed Parallel Computers. The Arrangement-Star network has many attractive topological properties such as small diameter, low degree, good connectivity, low broadcasting cost and flexibility in choosing the desired network size. Although, some of the research work has been done on Arrangement-Star network, it still needs more investigation and research efforts to explore these attractive topologies and utilize it to solve some real life applications. In this paper we attempt to fill this gap by proposing an efficient algorithm for load balancing among different processors of the Arrangement-Star network. The proposed algorithm is named as Arrangement Star Clustered Dimension Exchange Method ASCDEM presented and implemented on the Arrangement-Star network. The algorithm is based on the Clustered Dimension Exchange Method (CDEM). The ASCDEM algorithm is shown to be efficient in redistributing the load balancing among all different processors of the network as evenly as possible. A complete detail of this algorithm in addition to examples and discussions to explore the benefits of applying this distributed algorithm is presented in this paper. Furthermore an analytical study on the algorithm is presented and discussed to explore the attractive performance of the proposed algorithm.

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Section: Definitions and Topological Propertiesmentioning

confidence: 99%

Efficient Load Balancing Algorithm for the Arrangement-Star Network

Awwad¹,

Al-Sadi²

2016

ijacsa

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“…This set includes the following networks: hypercube, mesh, star graph [1], deBruijn network [19], product-shuffle network [18], hyper-Petersen network [4], mesh-connected-trees [8], hyper-deBruijn network [9], dBCube network [3], star-cube network [6], and hyperstar network [5]. We base our comparison on some of the most widely used criteria including network scalability, cost of broadcasting, embedding of other important topologies, cost/performance ratio, area of VLSI layout, and basic attributes of degree, diameter, and total number of links.…”

Section: Comparison Of Cartesian Product Networkmentioning

confidence: 99%

“…This framework covers a wide range of well-known topologies such as hypercubes, k-ary n-cubes, meshes, and generalized hypercubes. Based on this framework several other examples of product networks have been proposed and studied including hyperPetersen network [4], folded Petersen cube network [16], mesh-connected-trees [8], product-shuffle network [18], hyper-deBruijn network [9], star-cube network [6], and hyperstar network [5]. Rosenberg [18] studies the product-shuffle network (product of deBruijn graphs) and obtains embedding, network emulation, and VLSI layout results for this product network.…”

Section: Introductionmentioning

confidence: 98%

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Comparative Study of Product Networks

Al-Ayyoub

Day

2002

Journal of Parallel and Distributed Computing

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“…A large variety of network topologies have been proposed and studied for the interconnection of processors in parallel computing systems [1][2][3][4][5][6][7][8]. Among them hypercube has many desirable topological, algorithmic, and fault-tolerance properties.…”

Section: Introductionmentioning

confidence: 99%

Parallel Numerical Interpolation on Necklace Hypercubes

Meraji¹,

Sarbazi-Azad²

2007

First Asia International Conference on Modelling &Amp; Simulation (AMS'07)

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The Necklace Hypecube has been recently proposed as an attractive topology for multicomputers and was shown to have many desirable properties such as well-scalability and suitability for VLSI implementation. This paper introduces a parallel algorithm for computing an N-point Lagrange interpolation on a necklace hypercube multiprocessor. This algorithm consists of 3 phases: initialization, main and final. There is no computation in the initialization phase. The main phase consists of   / E steps (with E being the number of edges of the network), each consisting of 4 multiplications and 4 subtractions, and an additional step including 1 division and 1 multiplication. Communication in the main phase is based on an all-to-all broadcast algorithm using some Eulerian rings embedded in the host necklace hypercube. The finalphase is carried out in three sub-phases. There are   2 / k steps in the first sub-phase where k is the size of necklace. Each of sub-phases two and three contains n steps. Our study reveals that when implementation cost in taken into account, there is no speedup difference between lowdimensional and high-dimensional necklace networks.

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The Hyperstar Interconnection Network

Cited by 22 publications

References 40 publications

Efficient Load Balancing Algorithm for the Arrangement-Star Network

Efficient Load Balancing Algorithm for the Arrangement-Star Network

Comparative Study of Product Networks

Parallel Numerical Interpolation on Necklace Hypercubes

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