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Abstrak :
Pernrograman paralel pada mesin berbasis transputer dengan menggunakan peranti lunak bantu konvensional, seperti INMOS ANSI C, temyata cukup mempersulit pemakai. Kesulitan tersebut timbul karena pemakai harus mengetahui berbagai rnasalah teknis pemrograman dan aspek mesin dari transputer itu sendiri. Kesulitan tersebut dapat diatasi dengan membangun suatu wahana pemnograman paralel yang dapat rnenyembunyikan berbagai aspek teknis tersebut. Untuk mengatasi kesulitan tersebut, penulis melakukan penelitian yang bertujuan untuk membangun TransPVM, yaitu wahana pemrograrnan paralel berbasis message passing pada mesin berbasis tnnsuter, dengan mengimplernentasikan primitif-primitif dari Parallel Virtual Machine (PVM). Dengan TransPYM, pernrograman paralel dapat dinyatakan dalam sintaks PVM sehingga dapat diterapkan baik pada lingkungan PVM maupun TransPVM tanpa melakukan banyak perubahan pada program. Hasil yang diharapkan dari penelitian jul adalah: (1) TransPVM dapat memperrnudah pemrograman pada mesin berbasis transputer; (2) TransPVM dapat rnernpersingkat Ian gkah pemrograman yang diperlukan pada mesin berbasis transputer.

Abstrak :
This paper explains the development of a parallel computing platform using the available LAN at the Inter University Center for Computer Science of Indonesia. A software toll like parallel virtual machine enables the networked stations to be harnessed as a huge computing resource, combining various type of computing nodes to run parallel computing tasks. The research was aimed at first: to develop a number of parralel high complexity algorithms such as modelling air pollution distribution based on Gaussian Air Pollution Dispersion Formula which simulates dispersion of pollutant emiotted from industrial exhaust and also from vehicle exhaust ont the road. Secondly these algorithms were used to test the platform to obtain networkd behaviour in supporting the implementation of parallel algorithms. From the experiments conducted there are strong indications that the network based computing facility could be used as a suitable platform for running parallel programs with some restrictions. Optimum performance with near linear speed up could be obtained by carefully partitioning the problems, limiting message passing activities and balancing the load of the participating processors.

Abstrak :
This Springerbreif introduces a threshold-based channel sparsification approach, and then, the sparsity is exploited for scalable channel training. Last but not least, this brief introduces two scalable cooperative signal detection algorithms in C-RANs. The authors wish to spur new research activities in the following important question: how to leverage the revolutionary architecture of C-RAN to attain unprecedented system capacity at an affordable cost and complexity. Cloud radio access network (C-RAN) is a novel mobile network architecture that has a lot of significance in future wireless networks like 5G. the high density of remote radio heads in C-RANs leads to severe scalability issues in terms of computational and implementation complexities. This Springerbrief undertakes a comprehensive study on scalable signal processing for C-RANs, where scalable means that the computational and implementation complexities do not grow rapidly with the network size.