TY - GEN
T1 - Gain-cell embedded DRAMs
T2 - 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020
AU - Bonetti, Andrea
AU - Golman, Roman
AU - Giterman, Robert
AU - Teman, Adam
AU - Burg, Andreas
N1 - Publisher Copyright: © 2020 IEEE
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Among the different types of DRAMs, gain-cell embedded DRAM (GC-eDRAM) is a compact, low-power and CMOS-compatible alternative to conventional SRAM. GC-eDRAM achieves high memory density as it relies on a storage cell that can be implemented with as few as two transistors and that can be fabricated without additional process steps. However, since the performance of GC-eDRAMs relies on many interdependent variables, the optimization of the performance of these memories for the integration into their hosting system, as well as the design investigation of future GC-eDRAMs, prove to be highly complex tasks. In this context, modeling tools of memories are key enablers for the exploration of this large design space in a short amount of time. In this paper, we present GEMTOO, the first modeling tool that estimates timing, memory availability, bandwidth, and area of GC-eDRAMs. The tool considers parameters related to technology, circuits, and memory architecture and it enables the evaluation of architectural transformations as well as of advanced transistor-level effects, such as the increase of the access delay due to deterioration of the stored data. The timing is estimated with a maximum deviation of 15% from post-layout simulations in a 28 nm FD-SOI technology for different memory sizes and architectures. Moreover, the measured random cycle frequency of a GC-eDRAM fabricated in 28 nm CMOS bulk process is estimated with a 9% deviation when considering 6-sigma random process variations of the bitcells. The proposed GEMTOO modeling tool is used to show the intricacies in design optimization of GC-eDRAMs and, based on the results, optimal design practices are derived.
AB - Among the different types of DRAMs, gain-cell embedded DRAM (GC-eDRAM) is a compact, low-power and CMOS-compatible alternative to conventional SRAM. GC-eDRAM achieves high memory density as it relies on a storage cell that can be implemented with as few as two transistors and that can be fabricated without additional process steps. However, since the performance of GC-eDRAMs relies on many interdependent variables, the optimization of the performance of these memories for the integration into their hosting system, as well as the design investigation of future GC-eDRAMs, prove to be highly complex tasks. In this context, modeling tools of memories are key enablers for the exploration of this large design space in a short amount of time. In this paper, we present GEMTOO, the first modeling tool that estimates timing, memory availability, bandwidth, and area of GC-eDRAMs. The tool considers parameters related to technology, circuits, and memory architecture and it enables the evaluation of architectural transformations as well as of advanced transistor-level effects, such as the increase of the access delay due to deterioration of the stored data. The timing is estimated with a maximum deviation of 15% from post-layout simulations in a 28 nm FD-SOI technology for different memory sizes and architectures. Moreover, the measured random cycle frequency of a GC-eDRAM fabricated in 28 nm CMOS bulk process is estimated with a 9% deviation when considering 6-sigma random process variations of the bitcells. The proposed GEMTOO modeling tool is used to show the intricacies in design optimization of GC-eDRAMs and, based on the results, optimal design practices are derived.
KW - Computer-Aided design
KW - Embedded DRAM
KW - GEMTOO
KW - Gain cell
KW - Memory design
KW - Memory organization
KW - Modeling tool
UR - http://www.scopus.com/inward/record.url?scp=85109318764&partnerID=8YFLogxK
M3 - Conference contribution
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - 2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings
Y2 - 10 October 2020 through 21 October 2020
ER -