5,446 research outputs found
Plasmonic nanogap enhanced phase change devices with dual electrical-optical functionality
Modern-day computers use electrical signaling for processing and storing data
which is bandwidth limited and power-hungry. These limitations are bypassed in
the field of communications, where optical signaling is the norm. To exploit
optical signaling in computing, however, new on-chip devices that work
seamlessly in both electrical and optical domains are needed. Phase change
devices can in principle provide such functionality, but doing so in a single
device has proved elusive due to conflicting requirements of size-limited
electrical switching and diffraction-limited photonic devices. Here, we combine
plasmonics, photonics and electronics to deliver a novel integrated
phase-change memory and computing cell that can be electrically or optically
switched between binary or multilevel states, and read-out in either mode, thus
merging computing and communications technologies
Multilevel Simulation Methodology for FMECA Study Applied to a Complex Cyber-Physical System
Complex systems are composed of numerous interconnected subsystems, each designed
to perform specific functions. The different subsystems use many technological items that work
together, as for the case of cyber-physical systems. Typically, a cyber-physical system is composed
of different mechanical actuators driven by electrical power devices and monitored by sensors.
Several approaches are available for designing and validating complex systems, and among them,
behavioral-level modeling is becoming one of the most popular. When such cyber-physical systems
are employed in mission- or safety-critical applications, it is mandatory to understand the impacts of
faults on them and how failures in subsystems can propagate through the overall system. In this
paper, we propose a methodology for supporting the failure mode, effects, and criticality analysis
(FMECA) aimed at identifying the critical faults and assessing their effects on the overall system.
The end goal is to analyze how a fault affecting a single subsystem possibly propagates through
the whole cyber-physical system, considering also the embedded software and the mechanical
elements. In particular, our approach allows the analysis of the propagation through the whole
system (working at high level) of a fault injected at low level. This paper provides a solution to
automate the FMECA process (until now mainly performed manually) for complex cyber-physical
systems. It improves the failure classification effectiveness: considering our test case, it reduced the
number of critical faults from 10 to 6. The remaining four faults are mitigated by the cyber-physical
system architecture. The proposed approach has been tested on a real cyber-physical system in charge
of driving a three-phase motor for industrial compressors, showing its feasibility and effectiveness
Analog-digital simulation of transient-induced logic errors and upset susceptibility of an advanced control system
A simulation study is described which predicts the susceptibility of an advanced control system to electrical transients resulting in logic errors, latched errors, error propagation, and digital upset. The system is based on a custom-designed microprocessor and it incorporates fault-tolerant techniques. The system under test and the method to perform the transient injection experiment are described. Results for 2100 transient injections are analyzed and classified according to charge level, type of error, and location of injection
On the Verification of a WiMax Design Using Symbolic Simulation
In top-down multi-level design methodologies, design descriptions at higher
levels of abstraction are incrementally refined to the final realizations.
Simulation based techniques have traditionally been used to verify that such
model refinements do not change the design functionality. Unfortunately, with
computer simulations it is not possible to completely check that a design
transformation is correct in a reasonable amount of time, as the number of test
patterns required to do so increase exponentially with the number of system
state variables. In this paper, we propose a methodology for the verification
of conformance of models generated at higher levels of abstraction in the
design process to the design specifications. We model the system behavior using
sequence of recurrence equations. We then use symbolic simulation together with
equivalence checking and property checking techniques for design verification.
Using our proposed method, we have verified the equivalence of three WiMax
system models at different levels of design abstraction, and the correctness of
various system properties on those models. Our symbolic modeling and
verification experiments show that the proposed verification methodology
provides performance advantage over its numerical counterpart.Comment: In Proceedings SCSS 2012, arXiv:1307.802
Reliability in Power Electronics and Power Systems
L'abstract è presente nell'allegato / the abstract is in the attachmen
Recommended from our members
Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization.
The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product. While there have been many demonstrations of dot-product circuits and, separately, of stochastic neurons, the efficient hardware implementation combining both functionalities is still missing. Here we report compact, fast, energy-efficient, and scalable stochastic dot-product circuits based on either passively integrated metal-oxide memristors or embedded floating-gate memories. The circuit's high performance is due to mixed-signal implementation, while the efficient stochastic operation is achieved by utilizing circuit's noise, intrinsic and/or extrinsic to the memory cell array. The dynamic scaling of weights, enabled by analog memory devices, allows for efficient realization of different annealing approaches to improve functionality. The proposed approach is experimentally verified for two representative applications, namely by implementing neural network for solving a four-node graph-partitioning problem, and a Boltzmann machine with 10-input and 8-hidden neurons
- …