Indiana University-Purdue University Indianapolis (IUPUI) / Gopinath, Anoop. M.S.E.C.E., Purdue University, May 2018. Low-Power Hybrid
TFET-CMOS Memory. Major Professor: Maher E. Rizkalla.
The power consumption and the switching speed of the current CMOS technology
have reached their limits. In contrast, architecture design within computer systems
are continuously seeking more performance and e ciency. Advanced technologies that
optimize the power consumption and switching speed may help deliver this e ciency.
Indeed, beyond CMOS technology may be a viable approach to meeting the ever
increasing need for low-power design. These technology includes devices such as
Tunnel Field E ect Transistor (TFET), Graphene based devices such as GFET and
GRNFET and FinFET. However, the low cross-sectional area of the channel asso-
ciated with smaller technology nodes brings with it the challenges associated with
leakage current below the threshold. Mitigating these challenges with devices such as
TFETs may allow higher levels of integration, faster switching speed and lower power
consumption.
This thesis investigates the use of Gallium Nitride (GaN) TFET devices at 20nm
for memory cells. These cells can be used in the L1 data cache of the Graphic
Processing Units (GPU) thereby minimizing the static power and the dynamic power
within these memory systems. The TFET technology was chosen since it has a low
subthreshold slope of nearly 30mV/decade. This enables the TFET-based cells to
function with a 0.6V supply voltage leading to reduced dynamic power consumption
and leakage current when compared to the current CMOS technology.
The results suggest that there are bene ts in pursuing an integrated TFET-based
technology for Very Large Scale Integrated Circuit (VLSI) design. These bene ts are
demonstrated using simulation at the schematic-level using Cadence Virtuoso.
Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/15926 |
Date | 02 April 2018 |
Creators | Gopinath, Anoop |
Contributors | Rizkalla, Maher E. |
Source Sets | Indiana University-Purdue University Indianapolis |
Language | en_US |
Detected Language | English |
Type | Thesis |
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