3,413 research outputs found
Perspective: Organic electronic materials and devices for neuromorphic engineering
Neuromorphic computing and engineering has been the focus of intense research
efforts that have been intensified recently by the mutation of Information and
Communication Technologies (ICT). In fact, new computing solutions and new
hardware platforms are expected to emerge to answer to the new needs and
challenges of our societies. In this revolution, lots of candidates
technologies are explored and will require leveraging of the pro and cons. In
this perspective paper belonging to the special issue on neuromorphic
engineering of Journal of Applied Physics, we focus on the current achievements
in the field of organic electronics and the potentialities and specificities of
this research field. We highlight how unique material features available
through organic materials can be used to engineer useful and promising
bioinspired devices and circuits. We also discuss about the opportunities that
organic electronic are offering for future research directions in the
neuromorphic engineering field
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Nasics: A `Fabric-Centric\u27 Approach Towards Integrated Nanosystems
This dissertation addresses the fundamental problem of how to build computing systems for the nanoscale. With CMOS reaching fundamental limits, emerging nanomaterials such as semiconductor nanowires, carbon nanotubes, graphene etc. have been proposed as promising alternatives. However, nanoelectronics research has largely focused on a `device-first\u27 mindset without adequately addressing system-level capabilities, challenges for integration and scalable assembly.
In this dissertation, we propose to develop an integrated nano-fabric, (broadly defined as nanostructures/devices in conjunction with paradigms for assembly, inter-connection and circuit styles), as opposed to approaches that focus on MOSFET replacement devices as the ultimate goal. In the `fabric-centric\u27 mindset, design choices at individual levels are made compatible with the fabric as a whole and minimize challenges for nanomanufacturing while achieving system-level benefits vs. scaled CMOS.
We present semiconductor nanowire based nano-fabrics incorporating these fabric-centric principles called NASICs and N3ASICs and discuss how we have taken them from initial design to experimental prototype. Manufacturing challenges are mitigated through careful design choices at multiple levels of abstraction. Regular fabrics with limited customization mitigate overlay alignment requirements. Cross-nanowire FET devices and interconnect are assembled together as part of the uniform regular fabric without the need for arbitrary fine-grain interconnection at the nanoscale, routing or device sizing. Unconventional circuit styles are devised that are compatible with regular fabric layouts and eliminate the requirement for using complementary devices.
Core fabric concepts are introduced and validated. Detailed analyses on device-circuit co-design and optimization, cascading, noise and parameter variation are presented. Benchmarking of nanowire processor designs vs. equivalent scaled 16nm CMOS shows up to 22X area, 30X power benefits at comparable performance, and with overlay precision that is achievable with present-day technology. Building on the extensive manufacturing-friendly fabric framework, we present recent experimental efforts and key milestones that have been attained towards realizing a proof-of-concept prototype at dimensions of 30nm and below
Photonics design tool for advanced CMOS nodes
Recently, the authors have demonstrated large-scale integrated systems with
several million transistors and hundreds of photonic elements. Yielding such
large-scale integrated systems requires a design-for-manufacture rigour that is
embodied in the 10 000 to 50 000 design rules that these designs must comply
within advanced complementary metal-oxide semiconductor manufacturing. Here,
the authors present a photonic design automation tool which allows automatic
generation of layouts without design-rule violations. This tool is written in
SKILL, the native language of the mainstream electric design automation
software, Cadence. This allows seamless integration of photonic and electronic
design in a single environment. The tool leverages intuitive photonic layer
definitions, allowing the designer to focus on the physical properties rather
than on technology-dependent details. For the first time the authors present an
algorithm for removal of design-rule violations from photonic layouts based on
Manhattan discretisation, Boolean and sizing operations. This algorithm is not
limited to the implementation in SKILL, and can in principle be implemented in
any scripting language. Connectivity is achieved with software-defined
waveguide ports and low-level procedures that enable auto-routing of waveguide
connections.Comment: 5 pages, 10 figure
Asynchronous Nano-Electronics: Preliminary Investigation
This paper is a preliminary investigation in implementing
asynchronous QDI logic in molecular nano-electronics,
taking into account the restricted geometry, the lack of control
on transistor strengths, the high timing variations. We
show that the main building blocks of QDI logic can be successfully
implemented; we illustrate the approach with the
layout of an adder stage. The proposed techniques to improve
the reliability of QDI apply to nano-CMOS as well
Energy challenges for ICT
The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT
Memory and information processing in neuromorphic systems
A striking difference between brain-inspired neuromorphic processors and
current von Neumann processors architectures is the way in which memory and
processing is organized. As Information and Communication Technologies continue
to address the need for increased computational power through the increase of
cores within a digital processor, neuromorphic engineers and scientists can
complement this need by building processor architectures where memory is
distributed with the processing. In this paper we present a survey of
brain-inspired processor architectures that support models of cortical networks
and deep neural networks. These architectures range from serial clocked
implementations of multi-neuron systems to massively parallel asynchronous ones
and from purely digital systems to mixed analog/digital systems which implement
more biological-like models of neurons and synapses together with a suite of
adaptation and learning mechanisms analogous to the ones found in biological
nervous systems. We describe the advantages of the different approaches being
pursued and present the challenges that need to be addressed for building
artificial neural processing systems that can display the richness of behaviors
seen in biological systems.Comment: Submitted to Proceedings of IEEE, review of recently proposed
neuromorphic computing platforms and system
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