Conrad Mueller

Work place: School of Electrical and Information Engineering, The University of the Witwatersrand and School of IT Monash South Africa, Johannesburg

E-mail: cmueller@acm.org

Website:

Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Computer Networks, Data Structures and Algorithms

Biography

Dr Conrad Mueller is a research fellow in both the School of Electrical and Information Engineering: University of the Witwatersrand and in the School of IT: Monash South Africa. His research interests are programming languages, computer architectures and computer
science education with the main focus on new computational model that can contribute to these three fields. He received his PhD in Computer Science from The University of Witwatersrand. He had taught a wide range of courses in Computer Science. He is a member of the ACM and a fellow of the Institute of Computer Scientists and Information Technologists, South Africa.

Author Articles
Element-Based Computational Model

By Conrad Mueller

DOI: https://doi.org/10.5815/ijmecs.2012.01.01, Pub. Date: 8 Jan. 2012

A variation on the data-flow model is proposed to use for developing parallel architectures. While the model is a data driven model it has significant differences to the data- flow model. The proposed model has an evaluation cycle of processing elements (encapsulated data) that is similar to the instruction cycle of the von Neumann model. The elements contain the information required to process them. The model is inherently parallel. An emulation of the model has been implemented. The objective of this paper is to motivate support for taking the research further. Using matrix multiplication as a case study, the element/data-flow based model is compared with the instruction-based model. This is done using complexity analysis followed by empirical testing to verify this analysis. The positive results are given as motivation for the research to be taken to the next stage - that is, implementing the model using FPGAs.

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