  Data-intensive applications are poised to benefit directly from
processing-in-memory platforms, such as memristive Memory Processing Units,
which allow leveraging data locality and performing stateful logic operations.
Developing design automation flows for such platforms is a challenging and
highly relevant research problem. In this work, we investigate the problem of
minimizing delay under arbitrary area constraint for MAGIC-based in-memory
computing platforms. We propose an end-to-end area constrained technology
mapping framework, CONTRA. CONTRA uses Look-Up Table(LUT) based mapping of the
input function on the crossbar array to maximize parallel operations and uses a
novel search technique to move data optimally inside the array. CONTRA supports
benchmarks in a variety of formats, along with crossbar dimensions as input to
generate MAGIC instructions. CONTRA scales for large benchmarks, as
demonstrated by our experiments. CONTRA allows mapping benchmarks to smaller
crossbar dimensions than achieved by any other technique before, while allowing
a wide variety of area-delay trade-offs. CONTRA improves the composite metric
of area-delay product by 2.1x to 13.1x compared to seven existing technology
mapping approaches.
