125 research outputs found
Neuromorphic analogue VLSI
Neuromorphic systems emulate the organization and function of nervous systems. They are usually composed of analogue electronic circuits that are fabricated in the complementary metal-oxide-semiconductor (CMOS) medium using very large-scale integration (VLSI) technology. However, these neuromorphic systems are not another kind of digital computer in which abstract neural networks are simulated symbolically in terms of their mathematical behavior. Instead, they directly embody, in the physics of their CMOS circuits, analogues of the physical processes that underlie the computations of neural systems. The significance of neuromorphic systems is that they offer a method of exploring neural computation in a medium whose physical behavior is analogous to that of biological nervous systems and that operates in real time irrespective of size. The implications of this approach are both scientific and practical. The study of neuromorphic systems provides a bridge between levels of understanding. For example, it provides a link between the physical processes of neurons and their computational significance. In addition, the synthesis of neuromorphic systems transposes our knowledge of neuroscience into practical devices that can interact directly with the real world in the same way that biological nervous systems do
Technology Directions for the 21st Century
The Office of Space Communications (OSC) is tasked by NASA to conduct a planning process to meet NASA's science mission and other communications and data processing requirements. A set of technology trend studies was undertaken by Science Applications International Corporation (SAIC) for OSC to identify quantitative data that can be used to predict performance of electronic equipment in the future to assist in the planning process. Only commercially available, off-the-shelf technology was included. For each technology area considered, the current state of the technology is discussed, future applications that could benefit from use of the technology are identified, and likely future developments of the technology are described. The impact of each technology area on NASA operations is presented together with a discussion of the feasibility and risk associated with its development. An approximate timeline is given for the next 15 to 25 years to indicate the anticipated evolution of capabilities within each of the technology areas considered. This volume contains four chapters: one each on technology trends for database systems, computer software, neural and fuzzy systems, and artificial intelligence. The principal study results are summarized at the beginning of each chapter
CMOS-compatible Ising and Potts Annealing Using Single Photon Avalanche Diodes
Massively parallel annealing processors may offer superior performance for a
wide range of sampling and optimization problems. A key component dictating the
size of these processors is the neuron update circuit, ideally implemented
using special stochastic nanodevices. We leverage photon statistics using
single photon avalanche diodes (SPADs) and temporal filtering to generate
stochastic states. This method is a powerful alternative offering unique
features not currently seen in annealing processors: the ability to
continuously control the computational temperature and the seamless extension
to the Potts model, a -state generalization of the two-state Ising model.
SPADs also offer a considerable practical advantage since they are readily
manufacturable in current standard CMOS processes. As a first step towards
realizing a CMOS SPAD-based annealer, we have designed Ising and Potts models
driven by an array of discrete SPADs and show they accurately sample from their
theoretical distributions
Thermodynamic Computing
The hardware and software foundations laid in the first half of the 20th
Century enabled the computing technologies that have transformed the world, but
these foundations are now under siege. The current computing paradigm, which is
the foundation of much of the current standards of living that we now enjoy,
faces fundamental limitations that are evident from several perspectives. In
terms of hardware, devices have become so small that we are struggling to
eliminate the effects of thermodynamic fluctuations, which are unavoidable at
the nanometer scale. In terms of software, our ability to imagine and program
effective computational abstractions and implementations are clearly challenged
in complex domains. In terms of systems, currently five percent of the power
generated in the US is used to run computing systems - this astonishing figure
is neither ecologically sustainable nor economically scalable. Economically,
the cost of building next-generation semiconductor fabrication plants has
soared past $10 billion. All of these difficulties - device scaling, software
complexity, adaptability, energy consumption, and fabrication economics -
indicate that the current computing paradigm has matured and that continued
improvements along this path will be limited. If technological progress is to
continue and corresponding social and economic benefits are to continue to
accrue, computing must become much more capable, energy efficient, and
affordable. We propose that progress in computing can continue under a united,
physically grounded, computational paradigm centered on thermodynamics. Herein
we propose a research agenda to extend these thermodynamic foundations into
complex, non-equilibrium, self-organizing systems and apply them holistically
to future computing systems that will harness nature's innate computational
capacity. We call this type of computing "Thermodynamic Computing" or TC.Comment: A Computing Community Consortium (CCC) workshop report, 36 page
In-memory computing with emerging memory devices: Status and outlook
Supporting data for "In-memory computing with emerging memory devices: status and outlook", submitted to APL Machine Learning
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