ComPRIMe: A Compiler for Parallel and Scalable ReRAM-based In-Memory Computing

Steffen Frerix; Saeideh Shirinzadeh; Saman Fröhlich; Rolf Drechsler

In: Proceedings of the 15th IEEE / ACM International Symposium on Nanoscale Architectures. IEEE / ACM International Symposium on Nanoscale Architectures (NanoArch-2019), July 17-19, Qingdao, China, 2019.


In-memory computing is a promising solution for the issue of memory bottleneck in current computing systems. ReRAM is a non-volatile memory technology which natively implements basic logic operations and therefore enables to perform computational tasks. This allows to realize post von Neumann computer architectures with merged memory and processor. In this paper, we propose a fully automated compiler using andinverter graphs (AIGs) for a conventional in-memory computer architecture which supports parallel computation within regular ReRAM crossbar arrays. The proposed synthesis scheme optimizes crossbar mapping to increase parallelism and lower the number of memory reads and allocated ReRAM devices which results in considerable reductions in latency and area of inmemory implementations. Experimental results reveal minimum speed-ups of factor 2 compared to recent works while consuming a fraction of the ReRAM devices.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence