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Heterogeneous MPSoCs consisting of cores with different performance/power behaviors are widely used in many power-constrained real-time systems. Both soft-error reliability and lifetime reliability are key concerns in such systems. Although existing work have investigated related problems, they either focus on one of the two reliability concerns or propose complicated scheduling algorithms that cannot...
Many ultra-low power Internet of things (IoT) systems may be powered by energy harvested from ambient sources (e.g., solar radiation, thermal gradients, and WiFi). However, these energy sources can vary significantly in terms of their strengths and on/off patterns. For volatile systems, the intermittent nature of the energy sources necessitates the use of backup/recovery schemes to guarantee computational...
We consider how emerging transistor technologies, specifically ferroelectric field effect transistors (or FeFETs), can realize compact and energy efficient ternary content addressable memories (TCAMs). As Moore's Law-based performance scaling trends slow, and many computational tasks of interest are now more data-centric than compute-centric, researchers are looking to improve performance/save energy...
This paper discusses the development and evaluation of a Cellular Neural Network (CeNN) friendly deep learning network for solving the MNIST digit recognition problem. Prior work has shown that CeNNs leveraging emerging technologies such as tunnel transistors can improve energy or EDP of CeNNs, while simultaneously offering richer/more complex functionality. Important questions to address are what...
Tunneling field-effect transistors (TFETs) stand out among novel device technologies for low-power circuits and systems. While some TFETs exhibits behavior similar to MOSFETs, a group of emerging tunneling devices including symmetric tunneling FETs (SymFETs) and interlayer tunnel FETs (IFETs) demonstrate a bell-shaped I–V characteristic dissimilar to that of MOSFETs. They have shown the potential...
We discuss how the unique I–V characteristics offered by emerging, post-CMOS transistors can be used to enhance hardware security. Different from most existing work that exploits emerging technologies for hardware security, we (i) focus on transistor characteristics that either do not exist in, or are difficult to duplicate with MOSFETs, and (ii) aim to move beyond hardware implementations of physically...
Throughout the last decade, the microprocessor industry has been struggling to preserve the benefits of Moore's Law scaling. The persistent scaling of CMOS technology no longer yields exponential performance gains due in part to the growth of dark silicon. With each subsequent technology node generation, power constraints resulting from factors such as sub-threshold leakage currents are projected...
We consider the design of stochastic computing (SC) hardware based on spintronic devices. SC offers low-cost implementations of arithmetic operations and high degrees of error tolerance. When compared to charge-based devices, spin-based devices could be lower energy, nonvolatile, etc. However, spin-based devices can be fundamentally more error prone than charge-based devices. The marriage of SC architectures...
We consider how the I-V characteristics of emerging transistors (particularly those sponsored by STARnet) might be employed to enhance hardware security. An emphasis of this work is to move beyond hardware implementations of physically unclonable functions (PUFs) and random number generators (RNGs). We highlight how new devices (i) may enable more sophisticated logic obfuscation for IP protection,...
CMOS scaling has greatly increased concerns for lifetime reliability due to permanent faults and soft-error reliability due to transient faults. Most existing works only focus on one of the two reliability concerns, but often times techniques used to increase one type of reliability may adversely impact the other type. A few efforts do consider both types of reliability together and use two different...
Data integrity is important. One way to protect data integrity is attaching an identifying tag to individual data. The authenticity of the data can then be checked against its tag. If the data is altered by the adversary, the related tag becomes invalid and the attack will be detected. This paper studies an existing tag design (CETD) for memory data in embedded processor systems, where data that are...
Cellular neural networks (CNNs) are a powerful analog architecture that can outperform traditional von Neumann architecture for spatio-temporal information processing applications, e.g., image processing and speech recognition. Much existing work reports energy dissipation for CNNs at the chip level, which includes dissipation of sensors, actuators, and other components. As such, the impacts of various...
Source degeneration of access devices in the parallel (P)_ anti-parallel (AP) switching in Spin Transfer Torque Magnetic Random Access Memories (STT-MRAM) has ultimately been a limiting factor in the operational speed of these types of memories. In this work, new architectures for memory single-cells and arrays of cells are presented that utilize Schottky-Barrier Silicon Nanowire Field Effect Transistors...
Nanomagnetic logic (NML) is a “beyond-CMOS” technology that uses bistable magnets to store, process, and move binary information. Compared to CMOS, NML has several advantages such as non-volatility, lower power consumption, and radiation hardness. Recently, NML devices with perpendicular magnetic anisotropy (pNML) have been experimentally demonstrated to perform logic operations in three dimensions...
Novel devices are under investigation to extend the performance scaling trends that have long been associated with Moore's Law-based device scaling. Among the emerging devices being studied, tunnel FETs (or TFETs) are particularly attractive, especially when targeting low power systems. This paper studies the potential of analog/mixed-signal information processing using TFETs. The design of a highly-parallel...
Hardware security concerns such as IP piracy and hardware Trojans have triggered research into circuit protection and malicious logic detection from various design perspectives. In this paper, emerging technologies are investigated by leveraging their unique properties for applications in the hardware security domain. Three example circuit structures including camouflaging gates, polymorphic gates...
Traditional CMOS based von Neumann architectures face daunting challenges in performing complex computational tasks at high speed and with low power on spatio-temporal data, e.g., image processing, pattern recognition, etc. In this study, we discuss the utilities of various steep slope, beyond-CMOS emerging devices for image processing applications within the non-von Neumann computing paradigm of...
Solar-powered sensor nodes without specific energy maintenance have shown great promise in many applications, but they suffer from large energy storage and power converter loss. The storage-less and converter-less architecture with nonvolatile processing units has been proposed to reduce the energy loss. However, the architecture is sensitive to solar variations, since there is no energy buffering...
A Cellular Neural Network (CNN) is a highly-parallel, analog processor that can significantly outperform von Neumann architectures for certain classes of problems. Here, we show how emerging, beyond-CMOS devices could help to further enhance the capabilities of CNNs, particularly for solving problems with non-binary outputs. We show how CNNs based on devices such as graphene transistors — with multiple...
Nanomagnetic logic (NML) is a “beyond-CMOS” technology that combines logic and memory capabilities through field-coupled interactions between nanoscale magnets. NML is intrinsically non-volatile, low-power, and radiation-hard when compared to CMOS equivalents. Moreover, there have been numerous demonstrations of NML circuit functionality within the last decade. These fabricated structures typically...
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