IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems | Vol.37, Issue.7 | | Pages 1422-1435
Logic Synthesis for RRAM-Based In-Memory Computing
Design of nonvolatile in-memory computing devices has attracted high attention to resistive random access memories (RRAMs). We present a comprehensive approach for the synthesis of resistive in-memory computing circuits using binary decision diagrams, and-inverter graphs, and the recently proposed majority-inverter graphs for logic representation and manipulation. The proposed approach allows to perform parallel computing on a multirow crossbar architecture for the logic representations of the given Boolean functions throughout a level-by-level implementation methodology. It also provides alternative implementations utilizing two different logic operations for each representation, and optimizes them with respect to the number of RRAM devices and operations, addressing area, and delay, respectively. Experiments show that upper bounds of the aforementioned cost metrics for the implementations obtained by our synthesis approach are considerably improved in comparison with the corresponding existing methods in both area and especially latency.
Original Text (This is the original text for your reference.)
Logic Synthesis for RRAM-Based In-Memory Computing
Design of nonvolatile in-memory computing devices has attracted high attention to resistive random access memories (RRAMs). We present a comprehensive approach for the synthesis of resistive in-memory computing circuits using binary decision diagrams, and-inverter graphs, and the recently proposed majority-inverter graphs for logic representation and manipulation. The proposed approach allows to perform parallel computing on a multirow crossbar architecture for the logic representations of the given Boolean functions throughout a level-by-level implementation methodology. It also provides alternative implementations utilizing two different logic operations for each representation, and optimizes them with respect to the number of RRAM devices and operations, addressing area, and delay, respectively. Experiments show that upper bounds of the aforementioned cost metrics for the implementations obtained by our synthesis approach are considerably improved in comparison with the corresponding existing methods in both area and especially latency.
+More
binary decision diagrams andinverter graphs cost metrics delay multirow crossbar architecture parallel computing synthesis of resistive inmemory computing circuits especially latency area boolean functions synthesis approach logic representations levelbylevel implementation rram devices majorityinverter graphs resistive random access memories
Select your report category*
Reason*
New sign-in location:
Last sign-in location:
Last sign-in date: