Objective
Near Memory Computing: Major bottlenecks for future computation is the slow communication over slow interconnects between big data memories and big data processing and also the slow overhead of data memory accesses. The NeMeCo EID network aims at solving this problem by proposing fundamentally different architectures, integrating computation and memory, and using reconfigurable accelerators. Research topics of this project are: new, non-Von-Neumann architectures,
automated design of reconfigurable accelerators, advanced memory hierarchy based on both volatile and non-volatile memory components, and corresponding compiler, algorithmic optimization and mapping techniques.
Fields of science
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencesphysical sciencesastronomyobservational astronomyradio astronomy
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencescomputer and information sciencesdata sciencedata processing
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programme(s)
Funding Scheme
MSCA-ITN-EID - European Industrial Doctorates
Coordinator
5612 AE Eindhoven
Netherlands
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Participants (1)
8803 Rueschlikon
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