KIT | KIT-Bibliothek | Impressum | Datenschutz

A Spintronic 2M/7T Computation-in-Memory Cell

Jafari, Atousa 1; Münch, Christopher ORCID iD icon 1; Tahoori, Mehdi 1
1 Institut für Technische Informatik (ITEC), Karlsruher Institut für Technologie (KIT)

Abstract:

Computing data-intensive applications on the von Neumann architecture lead to significant performance and energy overheads. The concept of computation in memory (CiM) addresses the bottleneck of von Neumann machines by reducing the data movement in the computing system. Emerging resistive non-volatile memory technologies, as well as volatile memories (SRAM and DRAM), can be used to realize architectures based on the CiM paradigm. In this paper, we propose a hybrid cell design to provide the opportunity for CiM by combining the magnetic tunnel junction (MTJ) and the conventional 6T-SRAM cell. The cell performs CiM operations based on stateful in-array computation, which has better scalability for multiple operands compared with stateless computation in the periphery. Various logic operations such as XOR, OR, and IMP can be performed with the proposed design. In addition, the proposed cell can also operate as a conventional memory cell to read and write volatile as well as non-volatile data. The obtained simulation results show that the proposed CiM-A design can increase the performance of regular memory architectures by reducing the delay by 8 times and the energy by 13 times for database query applications consisting of consecutive bitwise operations with minimum overhead.


Zugehörige Institution(en) am KIT Institut für Technische Informatik (ITEC)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2079-9268
KITopen-ID: 1000156412
Erschienen in Journal of Low Power Electronics and Applications
Verlag MDPI
Band 12
Heft 4
Seiten 63
Bemerkung zur Veröffentlichung cited By 0
Vorab online veröffentlicht am 06.12.2022
Nachgewiesen in Dimensions
Scopus
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page