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Emerging memory devices enable performance improvements in memory applications and make possible chip designs using beyond von Neumann architectures. This paper explores the use of emerging memory devices in applications of nonvolatile logics and neuromorphic computing, and provides a review of several silicon examples of nonvolatile logics. This paper also discusses the challenges involved in the...
The training of neural network (NN) is usually time-consuming and resource intensive. Memristor has shown its potential in computation of NN. Especially for the metal-oxide resistive random access memory (RRAM), its crossbar structure and multi-bit characteristic can perform the matrix-vector product in high precision, which is the most common operation of NN. However, there exist two challenges on...
Placement is one of the most important techniques in modern field-programmable gate array design. Generally, analytical placement method optimizes the wire-length in global stage while allowing overlaps between blocks and is followed by a legalization step to remove all overlaps. In this paper, we propose a window based legalization method to remove all overlaps and place all instances at legalized...
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