A Study on Efficient Memory Utilization in Machine Learning and Memory Intensive Systems
As neural networks find more and more practical applications targeted for edge devices, the implementation of energy-efficient architectures is becoming very crucial. Despite the advancements in process technology, power and performance of memories remain to be a bottleneck for most computing platforms. The aim of this thesis is to study the effect of the breakdown structure of memories on power c
