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|Title:||Crossbar-constrained technology mapping for ReRAM based in-memory computing||Authors:||Bhattacharjee, Debjyoti
|Keywords:||Engineering::Computer science and engineering||Issue Date:||2020||Source:||Bhattacharjee, D., Tavva, Y., Easwaran, A. & Chattopadhyay, A. (2020). Crossbar-constrained technology mapping for ReRAM based in-memory computing. IEEE Transactions On Computers, 69(5), 734-748. https://dx.doi.org/10.1109/TC.2020.2964671||Journal:||IEEE Transactions on Computers||Abstract:||In-memory computing has gained significant attention due to the potential for dramatic improvement in speed and energy. Redox-based resistive RAMs (ReRAMs), capable of non-volatile storage and logic operations simultaneously have been used for logic-in-memory computing approaches. To this effect, we propose ReRAM based VLIW Architecture for in-Memory comPuting (ReVAMP), supported by a detailed device-accurate simulation setup with peripheral circuitry. We present theoretical bounds on the minimum area required for in-memory computation of arbitrary Boolean functions specified using structural representation (And-Inverter Graph and Majority-Inverter Graph) and two-level representation (Exclusive-Sum-of-Product). To support the ReVAMP architecture, we present two technology mapping flows that fully exploit the bit-level parallelism offered by the execution of logic using ReRAM crossbar array. The area-constrained mapping (ArC) generates feasible mapping for a variety of crossbar dimensions while the delay-constrained mapping (DeC) focuses primarily on minimizing the latency of mapping. We evaluate the proposed mappings against two state-of-the-art technology in-memory computing architectures, PLiM and MAGIC along with their automation flows (SIMPLE and COMPACT). ArC and DeC outperform state-of-the-art PLiM architecture by 1.46×1.46× and 4.3×4.3× on average in latency. ArC offers significantly lower area (on average 25.27×25.27× and 6.57×6.57×), while improving the area-delay product by 1.37×1.37× and 1.12×1.12× against two mapping approaches for MAGIC respectively. In contrast, DeC achieves average area (1.45×1.45× and 3.06×3.06×) and area-delay product (1.12×1.12× and 6.36×6.36×) improvements over the mapping approaches for MAGIC architecture respectively. The proposed mapping techniques allow a variety of runtime efficiency trade-offs.||URI:||https://hdl.handle.net/10356/154461||ISSN:||0018-9340||DOI:||10.1109/TC.2020.2964671||Rights:||© 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||SCSE Journal Articles|
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