This paper is presenting a discrete-event simulator written in C++ for modeling and simulating Fat tree network-on-chip systems based on MPLS technique. The simulator contains main component that construct butterfly Fat tree structure and other components that generate suitable number of switches and IP nodes (cores). The designed switch consists of input ports, output ports, input/output link controller, multi-buffers, crossbar switch, routing and arbitration components and MPLS unit. The correctness and the efficiency of the MPLS based Fat network-on-chip system is measured against well-known wormhole+ virtual channels technique. The produced results are clearly demonstrated the efficiency of the MPLS technique for future NoC designs. arabic 45 English 189
Azeddien M. Sllame, Nagwa Abobaker Salama(2-2018)

Deoxyribonucleic acid (DNA) micro-arrays present a powerful means of observing thousands of gene terms levels at the same time. They consist of high dimensional datasets, which challenge conventional clustering methods. The data’s high dimensionality calls for Self Organizing Maps (SOMs) to cluster DNA micro-array data. The DNA micro-array dataset are stored in huge biological databases for several purposes . The proposed methods are based on the idea of selecting a gene subset to distinguish all classes, it will be more effective to solve a multi-class problem, and we will propose a genetic programming (GP) based approach to analyze multi-class micro-array datasets. This biological dataset will be derived from multiple biological databases. The procedure responsible for extracting datasets called DNA-Aggregator. We will design a biological aggregator, which aggregates various datasets via DNA micro-array community-developed ontology based upon the concept of semantic Web for integrating and exchanging biological data. Our aggregator is composed of modules that retrieve the data from various biological databases. It will also enable queries by other applications to recognize the genes. The genes will be categorized in groups based on a classification method, which collects similar expression patterns. Using a clustering method such as k-mean is required either to discover the groups of similar objects from the biological database to characterize the underlying data distribution. arabic 10 English 60
Mariam Abojela Msaad, Zakaria Suliman Zubi(1-2010)

This paper presents a genetic based approach to the partitioning and mapping of multicore SoC cores over a NoC system that uses mesh topology. The proposed algorithm performs the partitioning and mapping by reducing communication cost and minimizing power consumption by placing those intercommunicated cores as close as possible together. A program developed in C++ in which the provided specification of the multicore MPSoC system captures all data dependencies before any start of the design process. Experimental results of several multimedia benchmarks demonstrates that the genetic-based approach able to find different satisfied implementations to the problem of partitioning and mapping of MPSoC cores over mesh-based NoC system that satisfies design goals
Azeddien M. Sllame, Walid Mokthar Salh(2-2021)