9 research outputs found
Memcomputing: a computing paradigm to store and process information on the same physical platform
In present day technology, storing and processing of information occur on
physically distinct regions of space. Not only does this result in space
limitations; it also translates into unwanted delays in retrieving and
processing of relevant information. There is, however, a class of two-terminal
passive circuit elements with memory, memristive, memcapacitive and
meminductive systems -- collectively called memelements -- that perform both
information processing and storing of the initial, intermediate and final
computational data on the same physical platform. Importantly, the states of
these memelements adjust to input signals and provide analog capabilities
unavailable in standard circuit elements, resulting in adaptive circuitry, and
providing analog massively-parallel computation. All these features are
tantalizingly similar to those encountered in the biological realm, thus
offering new opportunities for biologically-inspired computation. Of particular
importance is the fact that these memelements emerge naturally in nanoscale
systems, and are therefore a consequence and a natural by-product of the
continued miniaturization of electronic devices. We will discuss the various
possibilities offered by memcomputing, discuss the criteria that need to be
satisfied to realize this paradigm, and provide an example showing the solution
of the shortest-path problem and demonstrate the healing property of the
solution path.Comment: The first part of this paper has been published in Nature Physics 9,
200-202 (2013). The second part has been expanded and is now included in
arXiv:1304.167
Memristors for the Curious Outsiders
We present both an overview and a perspective of recent experimental advances
and proposed new approaches to performing computation using memristors. A
memristor is a 2-terminal passive component with a dynamic resistance depending
on an internal parameter. We provide an brief historical introduction, as well
as an overview over the physical mechanism that lead to memristive behavior.
This review is meant to guide nonpractitioners in the field of memristive
circuits and their connection to machine learning and neural computation.Comment: Perpective paper for MDPI Technologies; 43 page
Projective Embedding of Dynamical Systems: uniform mean field equations
We study embeddings of continuous dynamical systems in larger dimensions via
projector operators. We call this technique PEDS, projective embedding of
dynamical systems, as the stable fixed point of the dynamics are recovered via
projection from the higher dimensional space. In this paper we provide a
general definition and prove that for a particular type of projector operator
of rank-1, the uniform mean field projector, the equations of motion become a
mean field approximation of the dynamical system. While in general the
embedding depends on a specified variable ordering, the same is not true for
the uniform mean field projector. In addition, we prove that the original
stable fixed points remain stable fixed points of the dynamics, saddle points
remain saddle, but unstable fixed points become saddles.Comment: 45 pages; one column; 10 figures
Exploring Spin-transfer-torque devices and memristors for logic and memory applications
As scaling CMOS devices is approaching its physical limits, researchers have begun exploring newer devices and architectures to replace CMOS.
Due to their non-volatility and high density, Spin Transfer Torque (STT) devices are among the most prominent candidates for logic and memory applications. In this research, we first considered a new logic style called All Spin Logic (ASL). Despite its advantages, ASL consumes a large amount of static power; thus, several optimizations can be performed to address this issue. We developed a systematic methodology to perform the optimizations to ensure stable operation of ASL.
Second, we investigated reliable design of STT-MRAM bit-cells and addressed the conflicting read and write requirements, which results in overdesign of the bit-cells. Further, a Device/Circuit/Architecture co-design framework was developed to optimize the STT-MRAM devices by exploring the design space through jointly considering yield enhancement techniques at different levels of abstraction.
Recent advancements in the development of memristive devices have opened new opportunities for hardware implementation of non-Boolean computing. To this end, the suitability of memristive devices for swarm intelligence algorithms has enabled researchers to solve a maze in hardware. In this research, we utilized swarm intelligence of memristive networks to perform image edge detection. First, we proposed a hardware-friendly algorithm for image edge detection based on ant colony. Next, we designed the image edge detection algorithm using memristive networks
Natural Order: The Case for Applying Biomimetic Design Principles to Mass Communication Technology Design
In this paper I tested the effectiveness of a biomimetically designed classifier algorithm in an effort to support a new argument for the systemic application of biomimetic design principles to mass communication technology. To supplement the purely system-level test, I conducted a series of interviews with interface-level designers regarding their own design strategies, generally accepted design strategies in the field of mass communication technology design, new design strategies, and the landscape of the field in general. The findings of my test lend strong credence to biomimicry\u27s potential systemic contribution to mass communication technology design, and the tone of the interview responses suggests that the practices of interface-level design are congruent with this contribution. I argue that the placement of biomimetic design principles at the systemic level would enhance the user-interface design practices already in place, given their congruency with biomimetic design principles. I argue that to improve usability, interactivity, and security, and to improve our consumption, storage, and transmission of information on a massive scale, the most prudent course of action is to concentrate biomimetic design strategies systemically--into our hardware, networks, and systems in general--and that user-interface design would not only accommodate the changes to our system-level designs, but that it would thrive on them