Reliability analysis of MTJ-based functional module for neuromorphic computing
作者： Elena Ioana Vatajelu , Lorena Anghel
DOI: 10.1109/IOLTS.2017.8046207
关键词:
摘要: The power and reliability issues of today's memories limit the improvements attained by their implementation in scaled technology nodes. Several emergent memory technologies attempt to address technical constraints memories, amongst which, one most promising solutions is Spin-Transfer-Torque Magnetic Random Access Memories (STT-MRAMs). One great advantages emerging that they favor increasing system complexity performance. New applications computation paradigms, such as neuromorphic computing, unfeasible a few years back due technological limitations, can take profit from this technology. Intensive research has been conducted recently related magnetic device physics its dedicated hardware for however, little work evaluate circuits. In paper we investigate effect meaningful MTJ on behavior an MTJ-based Spiking Neural Network.
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