79 research outputs found
Quantum-dot Cellular Automata: Review Paper
Quantum-dot Cellular Automata (QCA) is one of the most important discoveries that will be the successful alternative for CMOS technology in the near future. An important feature of this technique, which has attracted the attention of many researchers, is that it is characterized by its low energy consumption, high speed and small size compared with CMOS. Inverter and majority gate are the basic building blocks for QCA circuits where it can design the most logical circuit using these gates with help of QCA wire. Due to the lack of availability of review papers, this paper will be a destination for many people who are interested in the QCA field and to know how it works and why it had taken lots of attention recentl
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Nanoelectronics-Biology Frontier: From Nanoscopic Probes for Action Potential Recording in Live Cells to Three-Dimensional Cyborg Tissues
Semiconductor nanowires configured as the active channels of field-effect transistors (FETs) have been used as detectors for high-resolution electrical recording from single live cells, cell networks, tissues and organs. Extracellular measurements with substrate supported silicon nanowire (SiNW) FETs, which have projected active areas orders of magnitude smaller than conventional microfabricated multielectrode arrays (MEAs) and planar FETs, recorded action potential and field potential signals with high signal-to-noise ratio and temporal resolution from cultured neurons, cultured cardiomyocytes, acute brain slices and whole animal hearts. Measurements made with modulation-doped nanoscale active channel SiNW FETs demonstrate that signals recorded from cardiomyocytes are highly localized and have improved time resolution compared to larger planar detectors. In addition, several novel three-dimensional (3D) transistor probes, which were realized using advanced nanowire synthesis methods, have been implemented for intracellular recording. These novel probes include (i) flexible 3D kinked nanowire FETs, (ii) branched intracellular nanotube SiNW FETs, and (iii) active silicon nanotube FETs. Following phospholipid modification of the probes to mimic the cell membrane, the kinked nanowire, branched intracellular nanotube and active silicon nanotube FET probes recorded full-amplitude intracellular action potentials from spontaneously firing cardiomyocytes. Moreover, these probes demonstrated the capability of reversible, stable, and long-term intracellular recording, thus indicating the minimal invasiveness of the new nanoscale structures and suggesting biomimetic internalization via the phospholipid modification. Simultaneous, multi-site intracellular recording from both single cells and cell networks were also readily achieved by interfacing independently addressable nanoprobe devices with cells. Finally, electronic and biological systems have been seamlessly merged in 3D for the first time using macroporous nanoelectronic scaffolds that are analogous to synthetic tissue scaffold and the extracellular matrix in tissue. Free-standing 3D nanoelectronic scaffolds were cultured with neurons, cardiomyocytes and smooth muscle cells to yield electronically-innervated synthetic or ‘cyborg’ tissues. Measurements demonstrate that innervated tissues exhibit similar cell viability as with conventional tissue scaffolds, and importantly, demonstrate that the real-time response to drugs and pH changes can be mapped in 3D through the tissues. These results open up a new field of research, wherein nanoelectronics are merged with biological systems in 3D thereby providing broad opportunities, ranging from a nanoelectronic/tissue platform for real-time pharmacological screening in 3D to implantable ‘cyborg’ tissues enabling closed-loop monitoring and treatment of diseases. Furthermore, the capability of high density scale-up of the above extra- and intracellular nanoscopic probes for action potential recording provide important tools for large-scale high spatio-temporal resolution electrical neural activity mapping in both 2D and 3D, which promises to have a profound impact on many research areas, including the mapping of activity within the brain.Chemistry and Chemical BiologyEngineering and Applied Science
Null Convention Logic applications of asynchronous design in nanotechnology and cryptographic security
This dissertation presents two Null Convention Logic (NCL) applications of asynchronous logic circuit design in nanotechnology and cryptographic security. The first application is the Asynchronous Nanowire Reconfigurable Crossbar Architecture (ANRCA); the second one is an asynchronous S-Box design for cryptographic system against Side-Channel Attacks (SCA). The following are the contributions of the first application: 1) Proposed a diode- and resistor-based ANRCA (DR-ANRCA). Three configurable logic block (CLB) structures were designed to efficiently reconfigure a given DR-PGMB as one of the 27 arbitrary NCL threshold gates. A hierarchical architecture was also proposed to implement the higher level logic that requires a large number of DR-PGMBs, such as multiple-bit NCL registers. 2) Proposed a memristor look-up-table based ANRCA (MLUT-ANRCA). An equivalent circuit simulation model has been presented in VHDL and simulated in Quartus II. Meanwhile, the comparison between these two ANRCAs have been analyzed numerically. 3) Presented the defect-tolerance and repair strategies for both DR-ANRCA and MLUT-ANRCA. The following are the contributions of the second application: 1) Designed an NCL based S-Box for Advanced Encryption Standard (AES). Functional verification has been done using Modelsim and Field-Programmable Gate Array (FPGA). 2) Implemented two different power analysis attacks on both NCL S-Box and conventional synchronous S-Box. 3) Developed a novel approach based on stochastic logics to enhance the resistance against DPA and CPA attacks. The functionality of the proposed design has been verified using an 8-bit AES S-box design. The effects of decision weight, bitstream length, and input repetition times on error rates have been also studied. Experimental results shows that the proposed approach enhances the resistance to against the CPA attack by successfully protecting the hidden key --Abstract, page iii
Performance analysis of fault-tolerant nanoelectronic memories
Performance growth in microelectronics, as described by Moore’s law, is steadily
approaching its limits. Nanoscale technologies are increasingly being explored as a
practical solution to sustaining and possibly surpassing current performance trends of
microelectronics. This work presents an in-depth analysis of the impact on performance,
of incorporating reliability schemes into the architecture of a crossbar molecular switch
nanomemory and demultiplexer. Nanoelectronics are currently in their early stages, and
so fabrication and design methodologies are still in the process of being studied and
developed. The building blocks of nanotechnology are fabricated using bottom-up
processes, which leave them highly susceptible to defects. Hence, it is very important that
defect and fault-tolerant schemes be incorporated into the design of nanotechnology
related devices.
In this dissertation, we focus on the study of a novel and promising class of
computer chip memories called crossbar molecular switch memories and their
demultiplexer addressing units. A major part of this work was the design of a defect and
fault tolerance scheme we called the Multi-Switch Junction (MSJ) scheme. The MSJ scheme takes advantage of the regular array geometry of the crossbar nanomemory to
create multiple switches in the fabric of the crossbar nanomemory for the storage of a
single bit.
Implementing defect and fault tolerant schemes come at a performance cost to the
crossbar nanomemory; the challenge becomes achieving a balance between device
reliability and performance. We have studied the reliability induced performance penalties
as they relate to the time (delay) it takes to access a bit, and the amount of power
dissipated by the process. Also, MSJ was compared to the banking and error correction
coding fault tolerant schemes. Studies were also conducted to ascertain the potential
benefits of integrating our MSJ scheme with the banking scheme. Trade-off analysis
between access time delay, power dissipation and reliability is outlined and presented in
this work.
Results show the MSJ scheme increases the reliability of the crossbar
nanomemory and demultiplexer. Simulation results also indicated that MSJ works very
well for smaller nanomemory array sizes, with reliabilities of 100% for molecular switch
failure rates in the 10% or less range
Architectural Solutions for NanoMagnet Logic
The successful era of CMOS technology is coming to an end. The limit on minimum fabrication dimensions of transistors and the increasing leakage power hinder the technological scaling that has characterized the last decades. In several different ways, this problem has been addressed changing the architectures implemented in CMOS, adopting parallel processors and thus increasing the throughput at the same operating frequency. However, architectural alternatives cannot be the definitive answer to a continuous increase in performance dictated by Moore’s law. This problem must be addressed from a technological point of view.
Several alternative technologies that could substitute CMOS in next years are currently under study. Among them, magnetic technologies such as NanoMagnet Logic (NML) are interesting because they do not dissipate any leakage power. More- over, magnets have memory capability, so it is possible to merge logic and memory in the same device.
However, magnetic circuits, and NML in this specific research, have also some important drawbacks that need to be addressed: first, the circuit clock frequency is limited to 100 MHz, to avoid errors in data propagation; second, there is a connection between circuit layout and timing, and in particular, longer wires will have longer latency. These drawbacks are intrinsic to the technology and for this reason they cannot be avoided. The only chance is to limit their impact from an architectural point of view.
The first step followed in the research path of this thesis is indeed the choice and optimization of architectures able to deal with the problems of NML. Systolic Ar- rays are identified as an ideal solution for this technology, because they are regular structures with local interconnections that limit the long latency of wires; more- over they are composed of several Processing Elements that work in parallel, thus exploit parallelization to increase throughput (limiting the impact of the low clock frequency). Through the analysis of Systolic Arrays for NML, several possible im- provements have been identified and addressed: 1) it has been defined a rigorous way to increase throughput with interleaving, providing equations that allow to esti- mate the number of operations to be interleaved and the rules to provide inputs; 2) a latency insensitive circuit has been designed, that exploits a data communication protocol between processing elements to avoid data synchronization problems. This feature has been exploited to design a latency insensitive Systolic Array that is able to execute the Floyd-Steinberg dithering algorithm. All the improvements presented in this framework apply to Systolic Arrays implemented in any technology. So, they can also be exploited to increase performance of today’s CMOS parallel circuits. This research path is presented in Chapter 3.
While Systolic Arrays are an interesting solution for NML, their usage could be quite limited because they are normally application-specific. The second re- search path addresses this problem. A Reconfigurable Systolic Array is presented, that can be programmed to execute several algorithms. This architecture has been tested implementing many algorithms, including FIR and IIR filters, Discrete Cosine Transform and Matrix Multiplication. This research path is presented in Chapter 4.
In common Von Neumann architectures, the logic part of the circuit and the memory one are separated. Today bus communication between logic and memory represents the bottleneck of the system. This problem is addressed presenting Logic- In-Memory (LIM), an architecture where memory elements are merged in logic ones. This research path aims at defining a real LIM architectures. This has been done in two steps. The first step is represented by an architecture composed of three layers: memory, routing and logic. In the second step instead the routing plane is no more present, and its features are inherited by the memory plane. In this solution, a pyramidal memory model is used, where memories near logic elements contain the most probably used data, and other memory layers contain the remaining data and instruction set. This circuit has been tested with odd-even sort algorithms and it has been benchmarked against GPUs and ASIC. This research path is presented in Chapter 5.
MagnetoElastic NML (ME-NML) is a technological improvement of the NML principle, proposed by researchers of Politecnico di Torino, where the clock system is based on the induced stretch of a piezoelectric substrate when a voltage is ap- plied to its boundaries. The main advantage of this solution is that it consumes much less power than the classic clock implementation. This technology has not yet been investigated from an architectural point of view and considering complex circuits. In this research field, a standard methodology for the design of ME-NML circuits has been proposed. It is based on a Standard Cell Library and an enhanced VHDL model. The effectiveness of this methodology has been proved designing a Galois Field Multiplier. Moreover the serial-parallel trade-off in ME-NML has been investigated, designing three different solutions for the Multiply and Accumulate structure. This research path is presented in Chapter 6.
While ME-NML is an extremely interesting technology, it needs to be combined with other faster technologies to have a real competitive system. Signal interfaces between NML and other technologies (mainly CMOS) have been rarely presented in literature. A mixed-technology multiplexer is designed and presented as the basis for a CMOS to NML interface. The reverse interface (from ME-NML to CMOS) is instead based on a sensing circuit for the Faraday effect: a change in the polarization of a magnet induces an electric field that can be used to generate an input signal for a CMOS circuit. This research path is presented in Chapter 7.
The research work presented in this thesis represents a fundamental milestone in the path towards nanotechnologies. The most important achievement is the de- sign and simulation of complex circuits with NML, benchmarking this technology with real application examples. The characterization of a technology considering complex functions is a major step to be performed and that has not yet been ad- dressed in literature for NML. Indeed, only in this way it is possible to intercept in advance any weakness of NanoMagnet Logic that cannot be discovered consid- ering only small circuits. Moreover, the architectural improvements introduced in this thesis, although technology-driven, can be actually applied to any technology. We have demonstrated the advantages that can derive applying them to CMOS cir- cuits. This thesis represents therefore a major step in two directions: the first is the enhancement of NML technology; the second is a general improvement of parallel architectures and the development of the new Logic-In-Memory paradigm
Cutting Edge Nanotechnology
The main purpose of this book is to describe important issues in various types of devices ranging from conventional transistors (opening chapters of the book) to molecular electronic devices whose fabrication and operation is discussed in the last few chapters of the book. As such, this book can serve as a guide for identifications of important areas of research in micro, nano and molecular electronics. We deeply acknowledge valuable contributions that each of the authors made in writing these excellent chapters
Memristive Computing
Memristive computing refers to the utilization of the memristor, the fourth
fundamental passive circuit element, in computational tasks.
The existence of the memristor was theoretically predicted in 1971 by
Leon O. Chua, but experimentally validated only in 2008 by HP Labs. A
memristor is essentially a nonvolatile nanoscale programmable resistor —
indeed, memory resistor — whose resistance, or memristance to be precise,
is changed by applying a voltage across, or current through, the device.
Memristive computing is a new area of research, and many of its fundamental
questions still remain open. For example, it is yet unclear which
applications would benefit the most from the inherent nonlinear dynamics
of memristors. In any case, these dynamics should be exploited to allow
memristors to perform computation in a natural way instead of attempting
to emulate existing technologies such as CMOS logic. Examples of such
methods of computation presented in this thesis are memristive stateful logic
operations, memristive multiplication based on the translinear principle, and
the exploitation of nonlinear dynamics to construct chaotic memristive circuits.
This thesis considers memristive computing at various levels of abstraction.
The first part of the thesis analyses the physical properties and the
current-voltage behaviour of a single device. The middle part presents memristor
programming methods, and describes microcircuits for logic and analog
operations. The final chapters discuss memristive computing in largescale
applications. In particular, cellular neural networks, and associative
memory architectures are proposed as applications that significantly benefit
from memristive implementation. The work presents several new results on
memristor modeling and programming, memristive logic, analog arithmetic
operations on memristors, and applications of memristors.
The main conclusion of this thesis is that memristive computing will
be advantageous in large-scale, highly parallel mixed-mode processing architectures.
This can be justified by the following two arguments. First,
since processing can be performed directly within memristive memory architectures,
the required circuitry, processing time, and possibly also power
consumption can be reduced compared to a conventional CMOS implementation.
Second, intrachip communication can be naturally implemented by
a memristive crossbar structure.Siirretty Doriast
MFPA: Mixed-Signal Field Programmable Array for Energy-Aware Compressive Signal Processing
Compressive Sensing (CS) is a signal processing technique which reduces the number of samples taken per frame to decrease energy, storage, and data transmission overheads, as well as reducing time taken for data acquisition in time-critical applications. The tradeoff in such an approach is increased complexity of signal reconstruction. While several algorithms have been developed for CS signal reconstruction, hardware implementation of these algorithms is still an area of active research. Prior work has sought to utilize parallelism available in reconstruction algorithms to minimize hardware overheads; however, such approaches are limited by the underlying limitations in CMOS technology. Herein, the MFPA (Mixed-signal Field Programmable Array) approach is presented as a hybrid spin-CMOS reconfigurable fabric specifically designed for implementation of CS data sampling and signal reconstruction. The resulting fabric consists of 1) slice-organized analog blocks providing amplifiers, transistors, capacitors, and Magnetic Tunnel Junctions (MTJs) which are configurable to achieving square/square root operations required for calculating vector norms, 2) digital functional blocks which feature 6-input clockless lookup tables for computation of matrix inverse, and 3) an MRAM-based nonvolatile crossbar array for carrying out low-energy matrix-vector multiplication operations. The various functional blocks are connected via a global interconnect and spin-based analog-to-digital converters. Simulation results demonstrate significant energy and area benefits compared to equivalent CMOS digital implementations for each of the functional blocks used: this includes an 80% reduction in energy and 97% reduction in transistor count for the nonvolatile crossbar array, 80% standby power reduction and 25% reduced area footprint for the clockless lookup tables, and roughly 97% reduction in transistor count for a multiplier built using components from the analog blocks. Moreover, the proposed fabric yields 77% energy reduction compared to CMOS when used to implement CS reconstruction, in addition to latency improvements
Dense implementations of binary cellular nonlinear networks : from CMOS to nanotechnology
This thesis deals with the design and hardware realization of the cellular neural/nonlinear network (CNN)-type processors operating on data in the form of black and white (B/W) images. The ultimate goal is to achieve a very compact yet versatile cell structure that would allow for building a network with a very large spatial resolution. It is very important to be able to implement an array with a great number of cells on a single die. Not only it improves the computational power of the processor, but it might be the enabling factor for new applications as well. Larger resolution can be achieved in two ways. First, the cell functionality and operating principles can be tailored to improve the layout compactness. The other option is to use more advanced fabrication technology – either a newer, further downscaled CMOS process or one of the emerging nanotechnologies.
It can be beneficial to realize an array processor as two separate parts – one dedicated for gray-scale and the other for B/W image processing, as their designs can be optimized. For instance, an implementation of a CNN dedicated for B/W image processing can be significantly simplified. When working with binary images only, all coefficients in the template matrix can also be reduced to binary values. In this thesis, such a binary programming scheme is presented as a means to reduce the cell size as well as to provide the circuits composed of emerging nanodevices with an efficient programmability. Digital programming can be very fast and robust, and leads to very compact coefficient circuits. A test structure of a binary-programmable CNN has been designed and implemented with standard 0.18 µm CMOS technology. A single cell occupies only 155 µm2, which corresponds to a cell density of 6451 cells per square millimeter. A variety of templates have been tested and the measured chip performance is discussed.
Since the minimum feature size of modern CMOS devices has already entered the nanometer scale, and the limitations of further scaling are projected to be reached within the next decade or so, more and more interest and research activity is attracted by nanotechnology. Investigation of the quantum physics phenomena and development of new devices and circuit concepts, which would allow to overcome the CMOS limitations, is becoming an increasingly important science. A single-electron tunneling (SET) transistor is one of the most attractive nanodevices. While relying on the Coulomb interactions, these devices can be connected directly with a wire or through a coupling capacitance. To develop suitable structures for implementing the binary programming scheme with capacitive couplings, the CNN cell based on the floating gate MOSFET (FG-MOSFET) has been designed. This approach can be considered as a step towards a programmable cell implementation with nanodevices. Capacitively coupled CNN has been simulated and the presented results confirm the proper operation. Therefore, the same circuit strategies have also been applied to the CNN cell designed for SET technology. The cell has been simulated to work well with the binary programming scheme applied. This versatile structure can be implemented either as a pure SET design or as a SET-FET hybrid. In addition to the designs mentioned above, a number of promising nanodevices and emerging circuit architectures are introduced.reviewe
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