11,928 research outputs found
Yield Enhancement of Digital Microfluidics-Based Biochips Using Space Redundancy and Local Reconfiguration
As microfluidics-based biochips become more complex, manufacturing yield will
have significant influence on production volume and product cost. We propose an
interstitial redundancy approach to enhance the yield of biochips that are
based on droplet-based microfluidics. In this design method, spare cells are
placed in the interstitial sites within the microfluidic array, and they
replace neighboring faulty cells via local reconfiguration. The proposed design
method is evaluated using a set of concurrent real-life bioassays.Comment: Submitted on behalf of EDAA (http://www.edaa.com/
A methodology for the generation of efficient error detection mechanisms
A dependable software system must contain error detection mechanisms and error recovery mechanisms. Software components for the detection of errors are typically designed based on a system specification or the experience of software engineers, with their efficiency typically being measured using fault injection and metrics such as coverage and latency. In this paper, we introduce a methodology for the design of highly efficient error detection mechanisms. The proposed methodology combines fault injection analysis and data mining techniques in order to generate predicates for efficient error detection mechanisms. The results presented demonstrate the viability of the methodology as an approach for the development of efficient error detection mechanisms, as the predicates generated yield a true positive rate of almost 100% and a false positive rate very close to 0% for the detection of failure-inducing states. The main advantage of the proposed methodology over current state-of-the-art approaches is that efficient detectors are obtained by design, rather than by using specification-based detector design or the experience of software engineers
Subcube embeddability and fault tolerance of augmented hypercubes
Hypercube networks have received much attention from both parallel processing and communications areas over the years since they offer a rich interconnection structure with high bandwidth, logarithmic diameter, and high degree of fault tolerance. They are easily partitionable and exhibit a high degree of fault tolerance. Fault-tolerance in hypercube and hypercube-based networks received the attention of several researchers in recent years; The primary idea of this study is to address and analyze the reliability issues in hypercube networks. It is well known that the hypercube can be augmented with one dimension to replace any of the existing dimensions should any dimension fail. In this research, it is shown that it is possible to add i dimensions to the standard hypercube, Qn to tolerate (i - 1) dimension failures, where 0 \u3c i ≤ n. An augmented hypercube, Qn +(n) with n additional dimensions is introduced and compared with two other hypercube networks with the same amount of redundancy. Reliability analysis for the three hypercube networks is done using the combinatorial and Markov modeling. The MTTF values are calculated and compared for all three networks. Comparison between similar size hypercube networks show that the augmented hypercube is more robust than the standard hypercube; As a related problem, we also look at the subcube embeddability. Subcube embeddability of the hypercube can be enhanced by introducing an additional dimension. A set of new dimensions, characterized by the Hamming distance between the pairs of nodes it connects, is introduced using a measure defined as the magnitude of a dimension. An enumeration of subcubes of various sizes is presented for a dimension parameterized by its magnitude. It is shown that the maximum number of subcubes for a Qn can only be attained when the magnitude of dimension is n - 1 or n. It is further shown that the latter two dimensions can optimally increase the number of subcubes among all possible choices
Fault Tolerant Adaptive Parallel and Distributed Simulation through Functional Replication
This paper presents FT-GAIA, a software-based fault-tolerant parallel and
distributed simulation middleware. FT-GAIA has being designed to reliably
handle Parallel And Distributed Simulation (PADS) models, which are needed to
properly simulate and analyze complex systems arising in any kind of scientific
or engineering field. PADS takes advantage of multiple execution units run in
multicore processors, cluster of workstations or HPC systems. However, large
computing systems, such as HPC systems that include hundreds of thousands of
computing nodes, have to handle frequent failures of some components. To cope
with this issue, FT-GAIA transparently replicates simulation entities and
distributes them on multiple execution nodes. This allows the simulation to
tolerate crash-failures of computing nodes. Moreover, FT-GAIA offers some
protection against Byzantine failures, since interaction messages among the
simulated entities are replicated as well, so that the receiving entity can
identify and discard corrupted messages. Results from an analytical model and
from an experimental evaluation show that FT-GAIA provides a high degree of
fault tolerance, at the cost of a moderate increase in the computational load
of the execution units.Comment: arXiv admin note: substantial text overlap with arXiv:1606.0731
Parallel Architectures for Planetary Exploration Requirements (PAPER)
The Parallel Architectures for Planetary Exploration Requirements (PAPER) project is essentially research oriented towards technology insertion issues for NASA's unmanned planetary probes. It was initiated to complement and augment the long-term efforts for space exploration with particular reference to NASA/LaRC's (NASA Langley Research Center) research needs for planetary exploration missions of the mid and late 1990s. The requirements for space missions as given in the somewhat dated Advanced Information Processing Systems (AIPS) requirements document are contrasted with the new requirements from JPL/Caltech involving sensor data capture and scene analysis. It is shown that more stringent requirements have arisen as a result of technological advancements. Two possible architectures, the AIPS Proof of Concept (POC) configuration and the MAX Fault-tolerant dataflow multiprocessor, were evaluated. The main observation was that the AIPS design is biased towards fault tolerance and may not be an ideal architecture for planetary and deep space probes due to high cost and complexity. The MAX concepts appears to be a promising candidate, except that more detailed information is required. The feasibility for adding neural computation capability to this architecture needs to be studied. Key impact issues for architectural design of computing systems meant for planetary missions were also identified
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