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dc.contributor.advisorTufte, Gunnarnb_NO
dc.contributor.authorJahren, Jon Emilnb_NO
dc.date.accessioned2014-12-19T13:39:06Z
dc.date.available2014-12-19T13:39:06Z
dc.date.created2012-11-08nb_NO
dc.date.issued2012nb_NO
dc.identifier566265nb_NO
dc.identifierntnudaim:7060nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/252986
dc.description.abstractEvolution in materio aim at revealing computational propertiesin materials. A bottom-up approach combining methods and theoriesfrom evolutionary algorithms, complex systems and unconventionalcomputation, is used to explore inherent computationalproperties of alternative computational materials. This master'sthesis build on earlier and ongoing research at NTNU focusingon interfacing materials. Mecobo is a prototype interface platform,including a physical interface, hardware for stimuli/measurementsand software, developed at NTNU.The Mecobo platform is intended to serve as a platform forexperimenting with unconventional materials' behavior in a dynamiccomplex system. This project describes the existing Mecoboplatform, modications to it and the new extension Cellular AutomataCentral Processing Unit (CA CPU). With the new extension,Mecobo is now capable of modelling dynamic complexsystems with a cellular automata and an unconventional material.The Cellular Automata Central Processing Unit extension is aparallel processor with 32 cores, but supports up to and including64 cores, for controlling each material conguration pin. Thecore is implemented as a stack machine optimized for instructionspace. It uses an 8-bit reduced instruction set computing (RISC)instruction set architecture (ISA).The modied Mecobo platform is tested and conrmed towork with several cellular automata rules and a simple modelconsisting of a theoretical material with constant response.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaim:7060no_NO
dc.subjectMTDT datateknikkno_NO
dc.subjectKomplekse datasystemerno_NO
dc.titleComputational Materials: Experimental Platformnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber113nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


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