1 research outputs found
Accurate Emulation of Memristive Crossbar Arrays for In-Memory Computing
In-memory computing is an emerging non-von Neumann computing paradigm where
certain computational tasks are performed in memory by exploiting the physical
attributes of the memory devices. Memristive devices such as phase-change
memory (PCM), where information is stored in terms of their conductance levels,
are especially well suited for in-memory computing. In particular, memristive
devices, when organized in a crossbar configuration can be used to perform
matrix-vector multiply operations by exploiting Kirchhoff's circuit laws. To
explore the feasibility of such in-memory computing cores in applications such
as deep learning as well as for system-level architectural exploration, it is
highly desirable to develop an accurate hardware emulator that captures the key
physical attributes of the memristive devices. Here, we present one such
emulator for PCM and experimentally validate it using measurements from a PCM
prototype chip. Moreover, we present an application of the emulator for neural
network inference where our emulator can capture the conductance evolution of
approximately 400,000 PCM devices remarkably well.Comment: 5 pages, 4 figures, accepted for publication at ISCAS 202