In-memory processing can dramatically improve
the latency and energy consumption of computing systems by
minimizing the data transfer between the memory and the
processor. Efficient execution of processing operations within the
memory is therefore a highly motivated objective in modern
computer architecture. This paper presents a novel automatic
framework for efficient implementation of arbitrary combinational logic functions within a memristive memory. Using tools
from logic design, graph theory and compiler register allocation
technology, we developed SIMPLER (Synthesis and In-memory
MaPping of Logic Execution in a single Row), a tool that
optimizes the execution of in-memory logic operations in terms
of throughput and area. Given a logical function, SIMPLER
automatically generates a sequence of atomic Memristor-Aided
loGIC (MAGIC) NOR operations and efficiently locates them
within a single size-limited memory row, reusing cells to save
area when needed. This approach fully exploits the parallelism
offered by the MAGIC NOR gates. It allows multiple instances of
the logic function to be performed concurrently, each compressed
into a single row of the memory. This virtue makes SIMPLER an
attractive candidate for designing in-memory Single Instruction,
Multiple Data (SIMD) operations. Compared to previous work
(that optimizes latency rather than throughput for a single
function), SIMPLER achieves an average throughput improvement of 435×. When previous tools are parallelized similarly to
SIMPLER, SIMPLER achieves higher throughput of at least 5×,
with 23× improvement in area and 20× improvement in area
efficiency. These improvements more than fully compensate for
the increase (up to 17% on average) in latency.
Modern Computer Architecture using different Technique
