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Design and Performance of an In-Memory Computing Architecture based on Phase-change Memory.
Rel. Gianluca Setti, Fabio Pareschi. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2020
Abstract
The von-Neumann architecture, still widely used nowadays, involves a physical division between the processing and memory unit which implies a large amount of data transfer leading to issues in terms of energy and latency, known as the Memory Wall. To overcome these problems, the memory and the processing unit must be collocated in a different way, passing to a non-von-Neumann architecture. This new kind of architecture is called In-Memory Computing (IMC), in which the separation between memory and processing unit for some computations is avoided. The Computational Memory is no more seen as a passive storage element but some logic is brought inside the memory itself so that specific computational tasks can be performed locally, saving energy and time.
In this thesis the computational task under analysis is the Matrix-Vector Multiplication (MVM), very used in some applications like the Compressed sensing (CS) or Deep Neural Network (DNN)
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