65 research outputs found
ToPoliNano and fiction: Design Tools for Field-coupled Nanocomputing
Field-coupled Nanocomputing (FCN) is a computing concept with several promising post-CMOS candidate implementations that offer tremendously low power dissipation and highest processing performance at the same time. Two of the manifold physical implementations are Quantum-dot Cellular Automata (QCA) and Nanomagnet Logic (NML). Both inherently come with domain-specific properties and design constraints that render established conventional design algorithms inapplicable. Accordingly, dedicated design tools for those technologies are required. This paper provides an overview of two leading examples of such tools, namely fiction and ToPoliNano. Both tools provide effective methods that cover aspects such as placement, routing, clocking, design rule checking, verification, and logical as well as physical simulation. By this, both freely available tools provide platforms for future research in the FCN domain
SCERPA Simulation of Clocked Molecular Field-Coupling Nanocomputing
Among all the possible technologies proposed for post-CMOS computing, molecular field-coupled nanocomputing (FCN) is one of the most promising technologies. The information propagation relies on electrostatic interactions among single molecules, overcoming the need for electron transport, significantly reducing energy dissipation. The expected working frequency is very high, and high throughput may be achieved by introducing an efficient pipeline of information propagation. The pipeline could be realized by adding an external clock signal that controls the propagation of data and makes the transmission adiabatic. In this article, we extend the Self-Consistent Electrostatic Potential Algorithm (SCERPA), previously introduced to analyze molecular circuits with a uniform clock field, to clocked molecular devices. The single-molecule is analyzed by ab initio calculations and modeled as an electronic device. Several clocked devices have been partitioned into clock zones and analyzed: the binary wire, the bus, the inverter, and the majority voter. The proposed modification of SCERPA enables linking the functional behavior of the clocked devices to molecular physics, becoming a possible tool for the eventual physical design verification of emerging FCN devices. The algorithm provides some first quantitative results that highlight the clocked propagation characteristics and provide significant feedback for the future implementation of molecular FCN circuits
Hybrid Quantum-Dot Cellular Automata Nanocomputing Circuits
Quantum-dot cellular automata (QCA) is an emerging transistor-less field-coupled nanocomputing (FCN) approach to ultra-scale ‘nanochip’ integration. In QCA, to represent digital circuitry, electrostatic repulsion between electrons and the mechanism of electron tunnelling in quantum dots are used. QCA technology can surpass conventional complementary metal oxide semiconductor (CMOS) technology in terms of clock speed, reduced occupied chip area, and energy efficiency. To develop QCA circuits, irreversible majority gates are typically used as the primary components. Recently, some studies have introduced reversible design techniques, using reversible majority gates as the main building block, to develop ultra-energy-efficient QCA circuits. However, this approach resulted in time delays, an increase in the number of QCA cells used, and an increase in the chip area occupied. This work introduces a novel hybrid design strategy employing irreversible, reversible, and partially reversible QCA gates to establish an optimal balance between power consumption, delay time, and occupied area. This hybrid technique allows the designer to have more control over the circuit characteristics to meet different system needs. A combination of reversible, irreversible, and innovative partially reversible majority gates is used in the proposed hybrid design method. We evaluated the hybrid design method by examining the half-adder circuit as a case study. We developed four hybrid QCA half-adder circuits, each of which simultaneously incorporates various types of majority gates. The QCADesigner-E 2.2 simulation tool was used to simulate the performance and energy efficiency of the half-adders. This tool provides numerical results for the circuit input/output response and heat dissipation at the physical level within a microscopic quantum mechanical model.N/
Modeling, Design, and Analysis of MagnetoElastic NML Circuits
With the predicted end of CMOS scaling process, researchers started to study several alternative technologies. Among them NanoMagnet Logic (NML) offers advantages complementary to MOS transistors especially for its magnetic nature. Its intrinsic memory capability makes it suitable for zero stand-by power and logic-in-memory applications. NML requires a clock system that, if based on a magnetic field, highly increases the circuit dynamic power consumption. We have recently proposed a solution based on the magnetoelastic effect (ME-NML) [1] and on currently available fabrication processes, which drastically reduces dynamic power consumption. However, many questions still remain unanswered. Which kind of applications are best suited for this technology? How can we effectively design, analyze, and compare ME-NML circuits? Does it really offer advantages over state-of-the-art CMOS transistors? In this paper, we provide answers to all these questions and the results prove that this technology offers indeed extremely good performance. We have designed a Galois field multiplier with a systolic array structure to reduce interconnection overhead. We developed a new RTL model that allows us to easily describe and simulate circuits of any complexity, evaluating at the same time the performance and keeping into account technology constraints. We approach for the first time in the NML scenario the design of ME-NML circuits adopting the standard-cell method used in standard technologies and fulfill the design down to the physical level. The same circuit is designed also with NML technology based on magnetic fields and with a 28 nm low power CMOS bulk technology for comparison. The CMOS circuit is obtained through physical place&route with a commercial tool, providing, therefore, the most accurate comparison ever presented in literature. Power analysis shows that ME-NML circuits have a considerable advantage over both NML and state-of-the-art CMOS bulk technology. As a further by-product results clearly highlight which kind of architectures can better exploit the true potential of NML technology
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Heat Dissipation Bounds for Nanocomputing: Methodology and Applications
Heat dissipation is a critical challenge facing the realization of emerging nanocomputing technologies. There are different components of this dissipation, and a part of it comes from the unavoidable cost of implementing logically irreversible operations. This stems from the fact that information is physical and manipulating it irreversibly requires energy. The unavoidable dissipative cost of losing information irreversibly fixes the fundamental limit on the minimum energy cost for computational strategies that utilize ubiquitous irreversible information processing.
A relation between the amount of irreversible information loss in a circuit and the associated energy dissipation was formulated by Landauer\u27s Principle in a technology-independent form. In a computing circuit, in addition to the nformation-theoretic dissipation, other physical processes that take place in association with irreversible information loss may also have an unavoidable thermodynamic cost that originates from the structure and operation of the circuit. In conventional CMOS circuits such unavoidable costs constitute only a minute fraction of the total power budget, however, in nanocircuits, it may be of critical significance due to the high density and operation speeds required. The lower bounds on energy, when obtained by considering the irreversible information cost as well as unavoidable costs associated with the operation of the underlying computing paradigm, may provide insight into the fundamental limitations of emerging technologies. This motivates us to study the problem of determining heat dissipation of computation in a way that reveals fundamental lower bounds on the energy cost for circuits realized in new computing paradigms.
In this work, we propose a physical-information-theoretic methodology that enables us to obtain such bounds for the minimum energy requirements of computation for concrete circuits realized within specific paradigms, and illustrate its application via prominent nanacomputing proposals. We begin by introducing the unavoidable heat dissipation problem and emphasize the significance of limitations it imposes on emerging technologies. We present the methodology developed to obtain the lower bounds on the unavoidable dissipation cost of computation for nanoelectronic circuits. We demonstrate our methodology via its application to various non-transistor-based (e.g. QCA) and transistor-based (e.g. NASIC) nanocomputing circuits. We also employ two CMOS circuits, in order to provide further insight into the application of our methodology by using this well-known conventional paradigm. We expand our methodology to modularize the dissipation analysis for QCA and NASIC paradigms, and discuss prospects for automation. We also revisit key concepts in thermodynamics of computation by focusing on the criticisms raised against the validity of Landauer\u27s Principle. We address these arguments and discuss their implications for our methodology. We conclude by elaborating possible directions towards which this work can be expanded
Design and Investigation of Genetic Algorithmic and Reinforcement Learning Approaches to Wire Crossing Reductions for pNML Devices
Perpendicular nanomagnet logic (pNML) is an emerging post-CMOS technology which encodes binary data in the polarization of single-domain nanomagnets and performs operations via fringing field interactions. Currently, there is no complete top-down workflow for pNML. Researchers must instead simultaneously handle place-and-route, timing, and logic minimization by hand. These tasks include multiple NP-Hard subproblems, and the lack of automated tools for solving them for pNML precludes the design of large-scale pNML circuits
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