Destiny: A comprehensive tool with 3D and multi-level cell memory modeling capability

Sparsh Mittal, Rujia Wang, Jeffrey Vetter

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

To enable the design of large capacity memory structures, novel memory technologies such as non-volatile memory (NVM) and novel fabrication approaches, e.g., 3D stacking and multi-level cell (MLC) design have been explored. The existing modeling tools, however, cover only a few memory technologies, technology nodes and fabrication approaches. We present DESTINY, a tool for modeling 2D/3D memories designed using SRAM, resistive RAM (ReRAM), spin transfer torque RAM (STT-RAM), phase change RAM (PCM) and embedded DRAM (eDRAM) and 2D memories designed using spin orbit torque RAM (SOT-RAM), domain wall memory (DWM) and Flash memory. In addition to single-level cell (SLC) designs for all of these memories, DESTINY also supports modeling MLC designs for NVMs. We have extensively validated DESTINY against commercial and research prototypes of these memories. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g., latency, area or energy-delay product) for a given memory technology, choosing the suitable memory technology or fabrication method (i.e., 2D v/s 3D) for a given optimization target, etc. We believe that DESTINY will boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers. The latest source-code of DESTINY is available from the following git repository: https://bitbucket.org/sparsh_mittal/destiny_v2.

Original languageEnglish
Article number23
JournalJournal of Low Power Electronics and Applications
Volume7
Issue number3
DOIs
StatePublished - Sep 2017

Funding

Acknowledgments: Support for this work was provided by Science and Engineering Research Board (SERB), India, award number ECR/2017/000622 and Office of Advanced Scientific Computing Research in the U.S. Department of Energy. The authors thank Matt Poremba for his help in earlier stages of this work.

FundersFunder number
U.S. Department of Energy
Advanced Scientific Computing Research
Science and Engineering Research BoardECR/2017/000622

    Keywords

    • Cache
    • DRAM
    • DWM
    • Emerging memory technologies
    • Flash
    • Modeling tool
    • Non-volatile memory (NVM or NVRAM)
    • Open-source
    • PCM
    • ReRAM
    • SOT-RAM
    • SRAM
    • STT-RAM
    • eDRAM

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