the problems which arise during the gas-oil exploration process and require high-performance computing resources can be divided in two groups. the first group is seismic data processing, the second group is 3D reservo...
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ISBN:
(纸本)9783319670355;9783319670348
the problems which arise during the gas-oil exploration process and require high-performance computing resources can be divided in two groups. the first group is seismic data processing, the second group is 3D reservoir simulating for the exploration process optimization. For the each group of problems typical applications used in real technological process were chosen, and their behavior was examined on different computational architectures. Performed analysis shows that the applications of the first group have good scalability potential on the studied computational platforms, meanwhile for the applications of the second group the limit of the performance increasing is reached relatively fast.
Robust object tracking is a crucial enabler of many computer vision applications. An embedded object tracker must, in addition to respecting real-time requirements, robustly update the position of the tracked object i...
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ISBN:
(纸本)9781450354875
Robust object tracking is a crucial enabler of many computer vision applications. An embedded object tracker must, in addition to respecting real-time requirements, robustly update the position of the tracked object in the captured images and be able to re-identify the object when it reappears after disappearing for a number of frames. To obtain such a robustness, modern algorithms such as the Tracking Learning Detection (TLD) combine classical tracking techniques with learning capabilities. this combination makes it possible to track an object's displacement, learn its new appearances when it changes orientation and re-identify it once it reappears. the strong performances of these techniques are obtained using costly computation that challenges hardware capabilities in the context of embedded architectures. this paper proposes a strategy for porting the TLD algorithm on an Field-Programmable Gate Array (FPGA). Based on parallel image resizing and selective object patch rejection, the proposed dataflow-oriented strategy demonstrates how the structure of the algorithm can be adapted to be more streaming-oriented and fit the structure of an FPGA. the results prove a tracking performance of up to 160 fps under 50Mhz for VGA images while keeping nearly the tracking robustness of the reference algorithm implementation.
A continuous formulation of the optimal 2-way graph partitioning based on the p-norm minimization of the graph Laplacian Rayleigh quotient is presented, which provides a sharp approximation to the balanced graph parti...
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ISBN:
(纸本)9781450358910
A continuous formulation of the optimal 2-way graph partitioning based on the p-norm minimization of the graph Laplacian Rayleigh quotient is presented, which provides a sharp approximation to the balanced graph partitioning problem, the optimality of which is known to be NP-hard. the minimization is initialized from a cut provided by a state-of-the-art multilevel recursive bisection algorithm, and then a continuation approach reduces the p-norm from a 2-norm towards a 1-norm, employing for each value of p a feasibility-preserving steepest-descent method that converges on the p-Laplacian eigenvector. A filter favors iterates advancing towards minimum edgecut and partition load imbalance. the complexity of the suggested approach is linear in graph edges. the simplicity of the steepest-descent algorithm renders the overall approach highly scalable and efficient in parallel distributed architectures. parallel implementation of recursive bisection on multi-core CPUs and GPUs are presented for large-scale graphs with up to 1.9 billion tetrahedra. the suggested approach exhibits improvements of up to 52.8% over METIS for graphs originating from triangular Delaunay meshes, 34.7% over METIS and 21.9% over KaHIP for power network graphs, 40.8% over METIS and 20.6% over KaHIP for sparse matrix graphs, and finally 93.2% over METIS for graphs emerging from social networks.
UML (Unified Modeling Language) is designed for all stages of software development, but it lacks precise semantic information. MDE (Model-driven engineering) takes the model as the primary software product and its mai...
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ISBN:
(纸本)9789811064425;9789811064418
UML (Unified Modeling Language) is designed for all stages of software development, but it lacks precise semantic information. MDE (Model-driven engineering) takes the model as the primary software product and its main research direction is modeling and model transformation. We propose to explore the entity abstraction scenario where no existing classes fit as the representative entity for other classes through the data, information and knowledge recreation of existing classes and relationships withthe introduction of knowledge graphs. In this paper, we proposed a knowledge graph to enhance model design between models.
Inventory management and supply chain are areas which have strong potential to benefit from Radio Frequency Identification technology. In the premises of a wholesale market, location tracking of a product itself becom...
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ISBN:
(纸本)9781538638521
Inventory management and supply chain are areas which have strong potential to benefit from Radio Frequency Identification technology. In the premises of a wholesale market, location tracking of a product itself becomes challenging for the buyers. the implemented application will help the buyer to locate required product and find the shortest path from his location to the product's location. this will help him to locate the product in optimum time, thus saving his efforts in searching the product manually. the location tracking is developed withthe RFID technology and shortest path is obtained through Digital Image processing.
the proceedings contain 90 papers. the special focus in this conference is on Information Systems and Technologies. the topics include: System dynamics modeling for the complexity of knowledge creation within adaptive...
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ISBN:
(纸本)9783319565347
the proceedings contain 90 papers. the special focus in this conference is on Information Systems and Technologies. the topics include: System dynamics modeling for the complexity of knowledge creation within adaptive large programs management;data base processing programs with using extended base semantic hypergraph;assessment of academic digital platform through social networks in economics degree;selection of information sources using a genetic algorithm;knowledge management and engineering approach concepts to capture organizational learning networks;detection of troublesome cases;semantic capture analysis in word embedding vectors using convolutional neural network;describing and comparing big data querying tools;artificial neural network for incremental data mining;detecting malicious components in large-scale internet-of-things systems and architectures;trajectory learning using principal component analysis;a recommendation system for online courses;a combination of regression techniques and cuckoo search algorithm for FOREX speculation;decision support systems based on knowledge management;exercise generation on language specification;automatic parallel data mining after bilingual document alignment;anti-bribery quantitative model for information systems based on human subjectivity;air dehumidifier controlled by arduino using peltier;life cycle of virtual organizations in the Czech republic;a governance model for managing lightweight IT;dynamic web information foraging using self-interested agents;open source CRM tools for small companies;assessment of risk-based process models in academic environment and an approach for examining the value of open data solutions.
the advent of multicore processors requires to reconsider the design of high performance computing libraries to embrace portable and effective techniques of parallel software engineering. One of the most promising app...
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ISBN:
(纸本)9783319589435;9783319589428
the advent of multicore processors requires to reconsider the design of high performance computing libraries to embrace portable and effective techniques of parallel software engineering. One of the most promising approaches consists in abstracting an application as a directed acyclic graph (DAG) of tasks. While this approach has been popularized for shared memory environments by the OpenMP 4.0 standard where dependencies between tasks are automatically inferred, we investigate an alternative approach, capable of describing the DAG of task in a distributed setting, where task dependencies are explicitly encoded. So far this approach has been mostly used in the case of algorithms with a regular data access pattern and we show in this study that it can be efficiently applied to a higly irregular numerical algorithm such as a sparse multifrontal QR method. We present the resulting implementation and discuss the potential and limits of this approach in terms of productivity and effectiveness in comparison with more common parallelization techniques. Although at an early stage of development, preliminary results show the potential of the parallel programming model that we investigate in this work.
In parallel computing, a valid graph coloring yields a lock-free processing of the colored tasks, data points, etc., without expensive synchronization mechanisms. However, coloring is not free and the overhead can be ...
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In parallel computing, a valid graph coloring yields a lock-free processing of the colored tasks, data points, etc., without expensive synchronization mechanisms. However, coloring is not free and the overhead can be significant. In particular, for the bipartite-graph partial coloring (BGPC) and distance-2 graph coloring (D2GC) problems, which have various use-cases within the scientific computing and numerical optimization domains, the coloring overhead can be in the order of minutes with a single thread for many real-life *** this work, we propose parallelalgorithms for bipartite-graph partial coloring on shared-memory architectures. Compared to the existing shared-memory BGPC algorithms, the proposed ones employ greedier and more optimistic techniques that yield a better parallel coloring performance. In particular, on 16 cores, the proposed algorithms are more than 4x faster than their counterparts in the ColPack library which is, to the best of our knowledge, the only publicly-available coloring library for multicore architectures. In addition to BGPC, the proposed techniques are employed to devise parallel distance-2 graph coloring algorithms and similar performance improvements have been observed. Finally, we propose two costless balancing heuristics for BGPC that can reduce the skewness and imbalance on the cardinality of color sets (almost) for free. the heuristics can also be used for the D2GC problem and in general, they will probably yield a better color-based parallelization performance especially on many-core architectures.
the proceedings contain 49 papers. the topics discussed include: models and approaches for the safety and the security of distributed systems;redesign CloudRAID for flexible and secure enterprise file sharing over pub...
ISBN:
(纸本)9781450353038
the proceedings contain 49 papers. the topics discussed include: models and approaches for the safety and the security of distributed systems;redesign CloudRAID for flexible and secure enterprise file sharing over public cloud storage;a universal user revocation scheme with key-escrow resistant for Ciphertext-policy attribute-based access control systems;an enhanced parallel version of RSA public key crypto based algorithm using OpenMP;a model of a secure electronic voting system based on blind intermediaries using Russian cryptographic algorithms;privacy preserving two-server Diffie-Hellman key exchange protocol;attribute-based approach of defining the secure behavior of automata objects;network security architectures for VANET;tamperproof complex event processing in IoT devices using side channel information;integer overflow vulnerabilities detection in software binary code;a novel malware analysis for malware detection and classification using machine learning algorithms;collaborative representation of Grassmann manifold projection metric for robust multi-spectral face recognition;extended multi-spectral imaging for gender classification based on image set;parameters of the two-stage synchronization algorithm for the quantum key distribution system;abnormal leakage of energy in battery-based IoT-devices;a framework for data security in the cloud using collaborative intrusion detection scheme;and integration of role based access control with homomorphic cryptosystem for secure and controlled access of data in cloud.
Lagrangian Particle Dispersion Method (LPDM) is applied to model atmospheric dispersion of radioactive material in a meso-scale of a few tens of kilometers for site study purpose. Empirical relationships are used to d...
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Lagrangian Particle Dispersion Method (LPDM) is applied to model atmospheric dispersion of radioactive material in a meso-scale of a few tens of kilometers for site study purpose. Empirical relationships are used to determine the dispersion coefficient for various atmospheric stabilities. Diagnostic 3-D wind field is created based on data from a meteorological station using mass-conservation principle. Particles imitating radioactive pollutant are dispersed in the wind-field as a point source. Time-integrated air concentration is calculated using kernel density estimator (KDE) in the lowest layer of the atmosphere. parallel code is developed for GTX-660Ti GPU with a total of 1344 scalar processors using CUDA programming. Significant speedup of about 20 times is achieved compared to the serial version of the code while accuracy is kept at reasonable level. Only small differences in particle positions and grid doses are observed when using the same sets of random number and meteorological data in both CPU and GPU versions of the code.
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