Search results for " Parallel"

Integration of a structural features-based preclassifier and a man-machine interactive classifier for a fast multi-stroke character recognition

2003

A transputer-based parallel machine for handwritten character recognition is proposed. An algorithm based on structural features and on a tree classifier was used to accomplish the pre-classification of the unknown sample in order to speed up the recognition process. The algorithm for the final classification is based on the description of the strokes through Fourier descriptors. The learning phase is accomplished through a man-machine interactive process. The proposed system can expand its knowledge base. A special representation of this knowledge base is proposed in order to record a great amount of data in a suitable way. A fast multistroke handwritten isolated character recognition syst…

MIS: Macro Icon System to generate macro algorithms for image analysis in parallel processing

1993

M-VIF: A machine-vision based on information fusion

2002

The authors describe a new architecture for machine vision, which is based on information fusion approach. Its general design has been developed by using a formal computation model that integrates three main ingredients of the visual computation: the data, the models, and the algorithms. The hardware design and the software environment of M-VIF are also given. The simulation of M-VIF is under development on the HERMIA-machine.

Mobile agent application fields

2004

Publisher Summary Mobile agents are a recent paradigm for software design, which extends object oriented programming features. An agent can perform its task autonomously; a mobile agent can carry out complex tasks that require the agent to migrate from a network place to another one. Mobile agent application fields are many. It can replace web services in other cases, mobile agents and web services can be an effective solution together. The chapter discusses the three mobile agent application fields, which are: parallel and distributed computing, data mining and information retrieval, and networking. An overview of the development platforms is also discussed. Data mining and information ret…

Stragi

2006

Si ripercorre la vicenda delle stragi che hanno insanguinato il nostro Paese a partire dall'immediato secondo dopoguerra fino ai primi anni '90, mettendo in luce trame di potere i cui attori non sono stati ancora identificati.

Trattativa

2006

Se – come emerge dalle più recenti inchieste della magistratura – Cosa Nostra mantiene ancora oggi il controllo su un’estesa area del territorio nazionale, condizionandone le scelte politiche, soggiogandone l’economia e veicolando un’ingente mole di flussi finanziari dentro e fuori i confini dell’economia nazionale attraverso complesse operazioni di riciclaggio, allora è plausibile ipotizzare anche uno scenario in cui l’organizzazione mafiosa sia indotta a interferire direttamente – e non più in via mediata – con il mondo della politica e delle istituzioni, aspirando a proporsi quale autorevole soggetto politico, forte al punto da impegnare i poteri istituzionali in una trattativa, in una n…

A Spatial-Temporal Correlation Approach for Data Reduction in Cluster-Based Sensor Networks

2019

International audience; In a resource-constrained Wireless Sensor Networks (WSNs), the optimization of the sampling and the transmission rates of each individual node is a crucial issue. A high volume of redundant data transmitted through the network will result in collisions, data loss, and energy dissipation. This paper proposes a novel data reduction scheme, that exploits the spatial-temporal correlation among sensor data in order to determine the optimal sampling strategy for the deployed sensor nodes. This strategy reduces the overall sampling/transmission rates while preserving the quality of the data. Moreover, a back-end reconstruction algorithm is deployed on the workstation (Sink)…

SWAPHI: Smith-Waterman Protein Database Search on Xeon Phi Coprocessors

2014

The maximal sensitivity of the Smith-Waterman (SW) algorithm has enabled its wide use in biological sequence database search. Unfortunately, the high sensitivity comes at the expense of quadratic time complexity, which makes the algorithm computationally demanding for big databases. In this paper, we present SWAPHI, the first parallelized algorithm employing Xeon Phi coprocessors to accelerate SW protein database search. SWAPHI is designed based on the scale-and-vectorize approach, i.e. it boosts alignment speed by effectively utilizing both the coarse-grained parallelism from the many co-processing cores (scale) and the fine-grained parallelism from the 512-bit wide single instruction, mul…

Accelerating large-scale biological database search on Xeon Phi-based neo-heterogeneous architectures

2015

In this paper we present new parallelization techniques for searching large-scale biological sequence databases with the Smith-Waterman algorithm on Xeon Phi-based neoheterogenous architectures. In order to make full use of the compute power of both the multi-core CPU and the many-core Xeon Phi hardware, we use a collaborative computing scheme as well as hybrid parallelism. At the CPU side, we employ SSE intrinsics and multi-threading to implement SIMD parallelism. At the Xeon Phi side, we use Knights Corner vector instructions to gain more data parallelism. We have presented two dynamic task distribution schemes (thread level and device level) in order to achieve better load balancing. Fur…

cuBool: Bit-Parallel Boolean Matrix Factorization on CUDA-Enabled Accelerators

2018

Boolean Matrix Factorization (BMF) is a commonly used technique in the field of unsupervised data analytics. The goal is to decompose a ground truth matrix C into a product of two matrices A and $B$ being either an exact or approximate rank k factorization of C. Both exact and approximate factorization are time-consuming tasks due to their combinatorial complexity. In this paper, we introduce a massively parallel implementation of BMF - namely cuBool - in order to significantly speed up factorization of huge Boolean matrices. Our approach is based on alternately adjusting rows and columns of A and B using thousands of lightweight CUDA threads. The massively parallel manipulation of entries …