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Near Volatile and Non-Volatile Memory Processing in 3D Systems
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0001-7877-6712
2022 (English)In: IEEE Transactions on Emerging Topics in Computing, E-ISSN 2168-6750, Vol. 10, no 3, p. 1657-1664Article in journal (Refereed) Published
Abstract [en]

The cost of transferring data between the off-chip memory system and compute unit is the fundamental energy and performance bottleneck in modern computing systems. Furthermore, with the advent of emerging data-intensive applications and technology scaling, this bottleneck has continuously increased. To overcome these difficulties, Near Memory Processing (NMP) based on 3D die stacking becomes a potential technology to transform the computation-centric system towards memory-centric system. In this work, we explore the feasibility and efficacy of a NMP architecture based on an emerging Non-Volatile Memory technology (NVM) for data-intensive applications and compare it with the conventional 3D-stacked NMP architecture based on DRAM. We demonstrate the effectiveness of our approach with experimental results.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. Vol. 10, no 3, p. 1657-1664
Keywords [en]
3D-Stacked Memory Technologies, Bandwidth, Central Processing Unit, Computer architecture, Data-Intensive Applications, Emerging Non-Volatile Memory Technologies, Memory management, Near Memory Processing, Nonvolatile memory, Random access memory, Three-dimensional displays, Dynamic random access storage, Information management, Memory architecture, Program processors, Three dimensional displays, Three dimensional integrated circuits, 3D-stacked memory, 3d-stacked memory technology, Data-intensive application, Emerging Non-volatile memory technology, Memory technology, Memory-management, Non-volatile memory, Three-dimensional display, Nonvolatile storage
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-312322DOI: 10.1109/TETC.2021.3115495ISI: 000849264200036Scopus ID: 2-s2.0-85116867298OAI: oai:DiVA.org:kth-312322DiVA, id: diva2:1660140
Note

QC 20220916

Available from: 2022-05-23 Created: 2022-05-23 Last updated: 2022-09-16Bibliographically approved

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Ebrahimi, Masoumeh

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