550 research outputs found
Enhancing Deep Neural Networks Testing by Traversing Data Manifold
We develop DEEPTRAVERSAL, a feedback-driven framework to test DNNs.
DEEPTRAVERSAL first launches an offline phase to map media data of various
forms to manifolds. Then, in its online testing phase, DEEPTRAVERSAL traverses
the prepared manifold space to maximize DNN coverage criteria and trigger
prediction errors. In our evaluation, DNNs executing various tasks (e.g.,
classification, self-driving, machine translation) and media data of different
types (image, audio, text) were used. DEEPTRAVERSAL exhibits better performance
than prior methods with respect to popular DNN coverage criteria and it can
discover a larger number and higher quality of error-triggering inputs. The
tested DNN models, after being repaired with findings of DEEPTRAVERSAL, achieve
better accurac
Design Space Exploration and Resource Management of Multi/Many-Core Systems
The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends
Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures
This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.Siirretty Doriast
Addressing Complexity and Intelligence in Systems Dependability Evaluation
Engineering and computing systems are increasingly complex, intelligent, and open adaptive. When it comes to the dependability evaluation of such systems, there are certain challenges posed by the characteristics of “complexity” and “intelligence”. The first aspect of complexity is the dependability modelling of large systems with many interconnected components and dynamic behaviours such as Priority, Sequencing and Repairs. To address this, the thesis proposes a novel hierarchical solution to dynamic fault tree analysis using Semi-Markov Processes. A second aspect of complexity is the environmental conditions that may impact dependability and their modelling. For instance, weather and logistics can influence maintenance actions and hence dependability of an offshore wind farm. The thesis proposes a semi-Markov-based maintenance model called “Butterfly Maintenance Model (BMM)” to model this complexity and accommodate it in dependability evaluation. A third aspect of complexity is the open nature of system of systems like swarms of drones which makes complete design-time dependability analysis infeasible. To address this aspect, the thesis proposes a dynamic dependability evaluation method using Fault Trees and Markov-Models at runtime.The challenge of “intelligence” arises because Machine Learning (ML) components do not exhibit programmed behaviour; their behaviour is learned from data. However, in traditional dependability analysis, systems are assumed to be programmed or designed. When a system has learned from data, then a distributional shift of operational data from training data may cause ML to behave incorrectly, e.g., misclassify objects. To address this, a new approach called SafeML is developed that uses statistical distance measures for monitoring the performance of ML against such distributional shifts. The thesis develops the proposed models, and evaluates them on case studies, highlighting improvements to the state-of-the-art, limitations and future work
Time- and Communication-Efficient Overlay Network Construction via Gossip
We focus on the well-studied problem of distributed overlay network
construction. We consider a synchronous gossip-based communication model where
in each round a node can send a message of small size to another node whose
identifier it knows. The network is assumed to be reconfigurable, i.e., a node
can add new connections (edges) to other nodes whose identifier it knows or
drop existing connections. Each node initially has only knowledge of its own
identifier and the identifiers of its neighbors. The overlay construction
problem is, given an arbitrary (connected) graph, to reconfigure it to obtain a
bounded-degree expander graph as efficiently as possible. The overlay
construction problem is relevant to building real-world peer-to-peer network
topologies that have desirable properties such as low diameter, high
conductance, robustness to adversarial deletions, etc.
Our main result is that we show that starting from any arbitrary (connected)
graph on nodes and edges, we can construct an overlay network that
is a constant-degree expander in polylog rounds using only
messages. Our time and message bounds are both essentially optimal (up to
polylogarithmic factors). Our distributed overlay construction protocol is very
lightweight as it uses gossip (each node communicates with only one neighbor in
each round) and also scalable as it uses only messages, which is
sublinear in (even when is moderately dense). To the best of our
knowledge, this is the first result that achieves overlay network construction
in polylog rounds and messages. Our protocol uses graph sketches in
a novel way to construct an expander overlay that is both time and
communication efficient. A consequence of our overlay construction protocol is
that distributed computation can be performed very efficiently in this model.Comment: Slightly shortened abstrac
Teaching FPGA Security
International audienceTeaching FPGA security to electrical engineering students is new at graduate level. It requires a wide field of knowledge and a lot of time. This paper describes a compact course on FPGA security that is available to electrical engineering master's students at the Saint-Etienne Institute of Telecom, University of Lyon, France. It is intended for instructors who wish to design a new course on this topic. The paper reviews the motivation for the course, the pedagogical issues involved, the curriculum, the lab materials and tools used, and the results. Details are provided on two original lab sessions, in particular, a compact lab that requires students to perform differential power analysis of FPGA implementation of the AES symmetric cipher. The paper gives numerous relevant references to allow the reader to prepare a similar curriculum
An Exactly Solvable Phase-Field Theory of Dislocation Dynamics, Strain Hardening and Hysteresis in Ductile Single Crystals
An exactly solvable phase-field theory of dislocation dynamics, strain
hardening and hysteresis in ductile single crystals is developed. The theory
accounts for: an arbitrary number and arrangement of dislocation lines over a
slip plane; the long-range elastic interactions between dislocation lines; the
core structure of the dislocations resulting from a piecewise quadratic Peierls
potential; the interaction between the dislocations and an applied resolved
shear stress field; and the irreversible interactions with short-range
obstacles and lattice friction, resulting in hardening, path dependency and
hysteresis. A chief advantage of the present theory is that it is analytically
tractable, in the sense that the complexity of the calculations may be reduced,
with the aid of closed form analytical solutions, to the determination of the
value of the phase field at point-obstacle sites. In particular, no numerical
grid is required in calculations. The phase-field representation enables
complex geometrical and topological transitions in the dislocation ensemble,
including dislocation loop nucleation, bow-out, pinching, and the formation of
Orowan loops. The theory also permits the consideration of obstacles of varying
strengths and dislocation line-energy anisotropy. The theory predicts a range
of behaviors which are in qualitative agreement with observation, including:
hardening and dislocation multiplication in single slip under monotonic
loading; the Bauschinger effect under reverse loading; the fading memory
effect, whereby reverse yielding gradually eliminates the influence of previous
loading; the evolution of the dislocation density under cycling loading,
leading to characteristic `butterfly' curves; and others
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