  In-memory computing (IMC) has gained significant attention recently as it
attempts to reduce the impact of memory bottlenecks. Numerous schemes for
digital IMC are presented in the literature, focusing on logic operations.
Often, an application's description has data dependencies that must be
resolved. Contemporary IMC architectures perform read followed by write
operations for this purpose, which results in performance and energy penalties.
To solve this fundamental problem, this paper presents in-memory mirroring
(IMM). IMM eliminates the need for read and write-back steps, thus avoiding
energy and performance penalties. Instead, we perform data movement within
memory, involving row-wise and column-wise data transfers. Additionally, the
IMM scheme enables parallel cloning of entire row (word) with a complexity of
$\mathcal{O}(1)$. Moreover, our analysis of the energy consumption of the
proposed technique using resistive random-access memory crossbar and
experimentally validated JART VCM v1b model. The IMM increases energy
efficiency and shows 2$\times$ performance improvement compared to conventional
data movement methods.
