Simulação de reservatórios de petróleo em ambiente MPSoC

The constant increase of complexity in computer applications demands the development of more powerful hardware support for them. With processor's operational frequency reaching its limit, the most viable solution is the use of parallelism. Based on parallelism techniques and the progressive growth in the capacity of transistors integration in a single chip is the concept of MPSoCs (Multi-Processor System-on-Chip). MPSoCs will eventually become a cheaper and faster alternative to supercomputers and clusters, and applications developed for these high performance systems will migrate to computers equipped with MP-SoCs containing dozens to hundreds of computation cores. In particular, applications in the area of oil and natural gas exploration are also characterized by the high processing capacity required and would benefit greatly from these high performance systems. This work intends to evaluate a traditional and complex application of the oil and gas industry known as reservoir simulation, developing a solution with integrated computational systems in a single chip, with hundreds of functional unities. For this, as the STORM (MPSoC Directory-Based Platform) platform already has a shared memory model, a new distributed memory model were developed. Also a message passing library has been developed folowing MPI standard

Análise de desempenho da rede neural artificial do tipo multilayer perceptron na era multicore

Artificial neural networks are usually applied to solve complex problems. In problems with more complexity, by increasing the number of layers and neurons, it is possible to achieve greater functional efficiency. Nevertheless, this leads to a greater computational effort. The response time is an important factor in the decision to use neural networks in some systems. Many argue that the computational cost is higher in the training period. However, this phase is held only once. Once the network trained, it is necessary to use the existing computational resources efficiently. In the multicore era, the problem boils down to efficient use of all available processing cores. However, it is necessary to consider the overhead of parallel computing. In this sense, this paper proposes a modular structure that proved to be more suitable for parallel implementations. It is proposed to parallelize the feedforward process of an RNA-type MLP, implemented with OpenMP on a shared memory computer architecture. The research consistes on testing and analizing execution times. Speedup, efficiency and parallel scalability are analyzed. In the proposed approach, by reducing the number of connections between remote neurons, the response time of the network decreases and, consequently, so does the total execution time. The time required for communication and synchronization is directly linked to the number of remote neurons in the network, and so it is necessary to investigate which one is the best distribution of remote connections

Implementação paralela escalável e eficiente do algoritmo simplex padrão em arquitetura multicore

This work presents a scalable and efficient parallel implementation of the Standard Simplex algorithm in the multicore architecture to solve large scale linear programming problems. We present a general scheme explaining how each step of the standard Simplex algorithm was parallelized, indicating some important points of the parallel implementation. Performance analysis were conducted by comparing the sequential time using the Simplex tableau and the Simplex of the CPLEXR IBM. The experiments were executed on a shared memory machine with 24 cores. The scalability analysis was performed with problems of different dimensions, finding evidence that our parallel standard Simplex algorithm has a better parallel efficiency for problems with more variables than constraints. In comparison with CPLEXR , the proposed parallel algorithm achieved a efficiency of up to 16 times better

A influência da prática meditativa sobre parâmetros psicofisiológicos e tarefas de memória operacional em indivíduos saudáveis

Meditation is described as a method for improving attention and promoting psychological and emotional stability, presenting favourable results on memory and stress tolerance as well. Studies have shown differences in physiological and psychological measurements between meditators and non-meditators. The aim of this study was to investigate the influence of regular meditation practice on working memory, psychological measurements and quality of life of healthy practitioners. We carried out a comparative study with meditators and non-meditators. Working memory tests and standard inventories of life quality, anxiety, mood, sleep quality, depression and stress were applied. Our study showed that meditators presented better scores in parameters indicative of life quality, mood, depression and stress when compared with non-meditators. Moreover, there was a trend in best performance of meditators in memory tasks (forward digit span task and Hanoi tower). These findings corroborate other studies showing that regular meditation can provide an improvement in general quality of life and affecting positively the behavioral and attentional functions in individuals

Um protocolo de comunicação multicast na camada de aplicação com Consciência de Localização

Internet applications such as media streaming, collaborative computing and massive multiplayer are on the rise,. This leads to the need for multicast communication, but unfortunately group communications support based on IP multicast has not been widely adopted due to a combination of technical and non-technical problems. Therefore, a number of different application-layer multicast schemes have been proposed in recent literature to overcome the drawbacks. In addition, these applications often behave as both providers and clients of services, being called peer-topeer applications, and where participants come and go very dynamically. Thus, servercentric architectures for membership management have well-known problems related to scalability and fault-tolerance, and even peer-to-peer traditional solutions need to have some mechanism that takes into account member's volatility. The idea of location awareness distributes the participants in the overlay network according to their proximity in the underlying network allowing a better performance. Given this context, this thesis proposes an application layer multicast protocol, called LAALM, which takes into account the actual network topology in the assembly process of the overlay network. The membership algorithm uses a new metric, IPXY, to provide location awareness through the processing of local information, and it was implemented using a distributed shared and bi-directional tree. The algorithm also has a sub-optimal heuristic to minimize the cost of membership process. The protocol has been evaluated in two ways. First, through an own simulator developed in this work, where we evaluated the quality of distribution tree by metrics such as outdegree and path length. Second, reallife scenarios were built in the ns-3 network simulator where we evaluated the network protocol performance by metrics such as stress, stretch, time to first packet and reconfiguration group time

Efeitos da cafeína sobre a memória de saguis (Callithrix jacchus)

Caffeine is considered the most consumed psychostimulant in the world, presenting several central and peripheral effects. In the Central Nervous System the major effect occur by its antagonistic activity at the A1 and A2a subtypes of the adenosine receptors. These receptors are responsible for the slow-wave sleep induction, and their binding, caused by the consumption of foods and beverages that contain caffeine, cause behaviors like increase of alertness, mood and locomotion. The effects of caffeine on memory are still discussed because of the diversity of experimental protocols. Also, it does not have the same effects on all stages of the processing of memory - acquisition, consolidation and recall. Thus, using the marmoset (Callitrhix jacchus) as subject, we aim to evaluate the effects of caffeine on the memory of this primate through the conditioned place preference paradigm, where the animal selects a context by presence of food. This cognitive task consists of five phases. The first phase was two sessions of pre-exposure, in which they were evaluated for preference for any compartment of the apparatus. Then, we proceeded the training, conditioning the animals to the food-present context for 8 days. Then, there was administration of caffeine or placebo (10mg/kg) for 8 consecutive days, during the pre-sleep phase, where the 20 animals were distributed in two groups: placebo and repeated. The forth phase was one day of retraining, a re-exposure of the apparatus to the marmosets followed by the administration of caffeine (for the repeated group and a new group called abstinence) or placebo (for placebo and abstinence groups). Finally, was the test where we evaluated if the subjects learned where the food was present. Moreover, in this work we evaluate the existence of differences between females and males on the task, and the locomotor activity for the experimental groups. The results showed that in the pre-exposure phase the animals were habituated on the apparatus and did not present differences for any contexts. In training, they were able to learn the conditioning task, independent of gender. For the retraining, the two groups exhibited more interactions in rewarded context than that in non-rewarded context. Nevertheless, in the locomotor activity, the repeated group moved similarly in contact with the apparatus and outside of it. In the other hand, the animals of the placebo group moved more when in contact with the apparatus. In the test phase, the marmosets under influence of caffeine presented an increase in the locomotor activity when compared with the placebo group, corroborating works that show this increase in locomotion. In the learning evaluation, the continuous and abstinence groups had a bad performance in the task in relation to the placebo and acute groups. This suggests that the prolonged administration of caffeine disrupts the memories because it affected sleep, which is largely responsible offline processing of memories

An augmented reality pipeline to create scenes with coherent illumination using textured cuboids

Shadows and illumination play an important role when generating a realistic scene in computer graphics. Most of the Augmented Reality (AR) systems track markers placed in a real scene and retrieve their position and orientation to serve as a frame of reference for added computer generated content, thereby producing an augmented scene. Realistic depiction of augmented content with coherent visual cues is a desired goal in many AR applications. However, rendering an augmented scene with realistic illumination is a complex task. Many existent approaches rely on a non automated pre-processing phase to retrieve illumination parameters from the scene. Other techniques rely on specific markers that contain light probes to perform environment lighting estimation. This study aims at designing a method to create AR applications with coherent illumination and shadows, using a textured cuboid marker, that does not require a training phase to provide lighting information. Such marker may be easily found in common environments: most of product packaging satisfies such characteristics. Thus, we propose a way to estimate a directional light configuration using multiple texture tracking to render AR scenes in a realistic fashion. We also propose a novel feature descriptor that is used to perform multiple texture tracking. Our descriptor is an extension of the binary descriptor, named discrete descriptor, and outperforms current state-of-the-art methods in speed, while maintaining their accuracy.