992 resultados para algorithm Context
Resumo:
Scheduling tasks to efficiently use the available processor resources is crucial to minimizing the runtime of applications on shared-memory parallel processors. One factor that contributes to poor processor utilization is the idle time caused by long latency operations, such as remote memory references or processor synchronization operations. One way of tolerating this latency is to use a processor with multiple hardware contexts that can rapidly switch to executing another thread of computation whenever a long latency operation occurs, thus increasing processor utilization by overlapping computation with communication. Although multiple contexts are effective for tolerating latency, this effectiveness can be limited by memory and network bandwidth, by cache interference effects among the multiple contexts, and by critical tasks sharing processor resources with less critical tasks. This thesis presents techniques that increase the effectiveness of multiple contexts by intelligently scheduling threads to make more efficient use of processor pipeline, bandwidth, and cache resources. This thesis proposes thread prioritization as a fundamental mechanism for directing the thread schedule on a multiple-context processor. A priority is assigned to each thread either statically or dynamically and is used by the thread scheduler to decide which threads to load in the contexts, and to decide which context to switch to on a context switch. We develop a multiple-context model that integrates both cache and network effects, and shows how thread prioritization can both maintain high processor utilization, and limit increases in critical path runtime caused by multithreading. The model also shows that in order to be effective in bandwidth limited applications, thread prioritization must be extended to prioritize memory requests. We show how simple hardware can prioritize the running of threads in the multiple contexts, and the issuing of requests to both the local memory and the network. Simulation experiments show how thread prioritization is used in a variety of applications. Thread prioritization can improve the performance of synchronization primitives by minimizing the number of processor cycles wasted in spinning and devoting more cycles to critical threads. Thread prioritization can be used in combination with other techniques to improve cache performance and minimize cache interference between different working sets in the cache. For applications that are critical path limited, thread prioritization can improve performance by allowing processor resources to be devoted preferentially to critical threads. These experimental results show that thread prioritization is a mechanism that can be used to implement a wide range of scheduling policies.
Resumo:
In a distributed model of intelligence, peer components need to communicate with one another. I present a system which enables two agents connected by a thick twisted bundle of wires to bootstrap a simple communication system from observations of a shared environment. The agents learn a large vocabulary of symbols, as well as inflections on those symbols which allow thematic role-frames to be transmitted. Language acquisition time is rapid and linear in the number of symbols and inflections. The final communication system is robust and performance degrades gradually in the face of problems.
Resumo:
We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. The performance of each expert may change over time in a manner unknown to the learner. We formulate a class of universal learning algorithms for this problem by expressing them as simple Bayesian algorithms operating on models analogous to Hidden Markov Models (HMMs). We derive a new performance bound for such algorithms which is considerably simpler than existing bounds. The bound provides the basis for learning the rate at which the identity of the optimal expert switches over time. We find an analytic expression for the a priori resolution at which we need to learn the rate parameter. We extend our scalar switching-rate result to models of the switching-rate that are governed by a matrix of parameters, i.e. arbitrary homogeneous HMMs. We apply and examine our algorithm in the context of the problem of energy management in wireless networks. We analyze the new results in the framework of Information Theory.
Resumo:
"Expectation-Maximization'' (EM) algorithm and gradient-based approaches for maximum likelihood learning of finite Gaussian mixtures. We show that the EM step in parameter space is obtained from the gradient via a projection matrix $P$, and we provide an explicit expression for the matrix. We then analyze the convergence of EM in terms of special properties of $P$ and provide new results analyzing the effect that $P$ has on the likelihood surface. Based on these mathematical results, we present a comparative discussion of the advantages and disadvantages of EM and other algorithms for the learning of Gaussian mixture models.
Resumo:
We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM's). Learning is treated as a maximum likelihood problem; in particular, we present an Expectation-Maximization (EM) algorithm for adjusting the parameters of the architecture. We also develop an on-line learning algorithm in which the parameters are updated incrementally. Comparative simulation results are presented in the robot dynamics domain.
Resumo:
Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprietary business processes, heterogeneous data standards, and diverse user requirements, it is critical that the services are implemented using adaptable, extensible, and scalable technology. The COntext INterchange (COIN) approach, inspired by similar goals of the Semantic Web, provides a robust solution. In this paper, we describe how COIN can be used to implement dynamic online services where semantic differences are reconciled on the fly. We show that COIN is flexible and scalable by comparing it with several conventional approaches. With a given ontology, the number of conversions in COIN is quadratic to the semantic aspect that has the largest number of distinctions. These semantic aspects are modeled as modifiers in a conceptual ontology; in most cases the number of conversions is linear with the number of modifiers, which is significantly smaller than traditional hard-wiring middleware approach where the number of conversion programs is quadratic to the number of sources and data receivers. In the example scenario in the paper, the COIN approach needs only 5 conversions to be defined while traditional approaches require 20,000 to 100 million. COIN achieves this scalability by automatically composing all the comprehensive conversions from a small number of declaratively defined sub-conversions.
Resumo:
The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Web – both at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.
Resumo:
The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.
Resumo:
The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.
Resumo:
The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.
Resumo:
The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.
Resumo:
The discontinuities in the solutions of systems of conservation laws are widely considered as one of the difficulties in numerical simulation. A numerical method is proposed for solving these partial differential equations with discontinuities in the solution. The method is able to track these sharp discontinuities or interfaces while still fully maintain the conservation property. The motion of the front is obtained by solving a Riemann problem based on the state values at its both sides which are reconstructed by using weighted essentially non oscillatory (WENO) scheme. The propagation of the front is coupled with the evaluation of "dynamic" numerical fluxes. Some numerical tests in 1D and preliminary results in 2D are presented.
Resumo:
Aquesta ponència tracta sobre la baixa participació estudiantil a les universitats públiques catalanes i l’experiència d’una assignatura pilot sobre participació estudiantil a la Universitat Pompeu Fabra (UPF). Primer, es fa una diagnosi de l’estat de la participació estudiantil per plantejar, entre algunes de les mesures per intentar incrementar la participació, la formació en aquest àmbit. En segon lloc, s’explica l’experiència pilot de la realització d’una assignatura de lliure elecció sobre participació estudiantil a la universitat des del procés d’elaboració del programa fins la implementació en dos cursos acadèmics. Es conclou amb una avaluació de l’experiència docent destacant els aspectes positius i les seves limitacions
Resumo:
L’adaptació a l’EEES comporta un canvi cultural per a les universitats de l’estat espanyol. Desde la perspectiva de la gestió del canvi organitzatiu, marc teòric en el que es sustenta aquest estudi, aquest canvi es pot categoritzar com una reorientació segons la classificació de Nadler i Tushman (1995), donat que es tracta d’un canvi profund, discontinu i radical que s’anticipa als canvis i necessitats de l’entorn. Aquest tipus de canvis requereixen d’una introducció gradual, donat que la seva magnitud qüestiona la identitat i cultura de l’organització, generant moltes resistències. Des d’aquesta literatura es recomana fer un diagnòstic de les forces que afecten al canvi per tal de garantir el seu èxit. En aquest sentit, l’objectiu del present estudi és la identificació de les forces inhibidores del canvi cultural en la URV a partir d’una anàlisi introspectiva de les experiència d’innovació docent en l’assignatura de Pràctiques Integrades I. La metodologia utilitzada per aquest estudi ha estat la introspecció personal subjectiva (Brown & Reid , 1997; Patterson et al., 1998; Holbrook, 2005). L’experiència consistia en l’avaluació de certes competències de saber, saber fer, i saber ser i estar, a través de diferents mètodes d’avaluació docent. Les dades de satisfacció dels estudiants amb la metodologia de l’assignatura es van recollir mitjançant un informe d’opinió anònim i no estructurat que se’ls demanava entregar l’últim dia de classe. Opinions més generals sobre el canvi a l’EEES es van recollir a l’inici de l’assignatura a través d’una sessió de focus group amb cada un dels grups d’activitat de l’assignatura. Son múltiples els estudis que afirmen la conveniència de posar en pràctica noves metodologies i formes d’innovació docent que situïn a l’alumne com a eix central de l’aprenentatge i que avaluïn els seus aprenentatges en funció de l’adquisició de competències (Apodaca, 2006, Bautista et al. 2007, Margalef i Canabal, 2007, Brown i Glasner, 2003). No obstant, els resultats del nostre estudi posen en evidència que una de les principals forces inhibidores per a la gestió del canvi en el sistema docent universitari son les actituds dels alumnes, i en especial les d’aquells alumnes que combinen simultàniament estudis amb l’activitat laboral. Com a resultat de l’anàlisi, es proposen mesures per neutralitzar o eliminar les resistències identificades i es duu a terme una reflexió sobre com s’està duent a terme la gestió del canvi en la universitat