Exploration and Design of Power-Efficient Networked Many-Core Systems

Multiprocessing is a promising solution to meet the requirements of near future applications. To get full benefit from parallel processing, a manycore system needs efficient, on-chip communication architecture. Networkon- Chip (NoC) is a general purpose communication concept that offers highthroughput, reduced power consumption, and keeps complexity in check by a regular composition of basic building blocks. This thesis presents power efficient communication approaches for networked many-core systems. We address a range of issues being important for designing power-efficient manycore systems at two different levels: the network-level and the router-level. From the network-level point of view, exploiting state-of-the-art concepts such as Globally Asynchronous Locally Synchronous (GALS), Voltage/ Frequency Island (VFI), and 3D Networks-on-Chip approaches may be a solution to the excessive power consumption demanded by today’s and future many-core systems. To this end, a low-cost 3D NoC architecture, based on high-speed GALS-based vertical channels, is proposed to mitigate high peak temperatures, power densities, and area footprints of vertical interconnects in 3D ICs. To further exploit the beneficial feature of a negligible inter-layer distance of 3D ICs, we propose a novel hybridization scheme for inter-layer communication. In addition, an efficient adaptive routing algorithm is presented which enables congestion-aware and reliable communication for the hybridized NoC architecture. An integrated monitoring and management platform on top of this architecture is also developed in order to implement more scalable power optimization techniques. From the router-level perspective, four design styles for implementing power-efficient reconfigurable interfaces in VFI-based NoC systems are proposed. To enhance the utilization of virtual channel buffers and to manage their power consumption, a partial virtual channel sharing method for NoC routers is devised and implemented. Extensive experiments with synthetic and real benchmarks show significant power savings and mitigated hotspots with similar performance compared to latest NoC architectures. The thesis concludes that careful codesigned elements from different network levels enable considerable power savings for many-core systems.Siirretty Doriast

Toward a More Accurate Web Service Selection Using Modified Interval DEA Models with Undesirable Outputs

With the growing number of Web services on the internet, there is a challenge to select the best Web service which can offer more quality-of-service (QoS) values at the lowest price. Another challenge is the uncertainty of QoS values over time due to the unpredictable nature of the internet. In this paper, we modify the interval data envelopment analysis (DEA) models [Wang, Greatbanks and Yang (2005)] for QoS-aware Web service selection considering the uncertainty of QoS attributes in the presence of desirable and undesirable factors. We conduct a set of experiments using a synthesized dataset to show the capabilities of the proposed models. The experimental results show that the correlation between the proposed models and the interval DEA models is significant. Also, the proposed models provide almost robust results and represent more stable behavior than the interval DEA models against QoS variations. Finally, we demonstrate the usefulness of the proposed models for QoS-aware Web service composition. Experimental results indicate that the proposed models significantly improve the fitness of the resultant compositions when they filter out unsatisfactory candidate services for each abstract service in the preprocessing phase. These models help users to select the best possible cloud service considering the dynamic internet environment and they help service providers to improve their Web services in the marke

Improving the Operation of Text Categorization Systems with Selecting Proper Features Based on PSO-LA

With the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. One of the major problems in text classification relates to the high dimensional feature spaces. Therefore, the main goal of text classification is to reduce the dimensionality of features space. There are many feature selection methods. However, only a few methods are utilized for huge text classification problems. In this paper, we propose a new wrapper method based on Particle Swarm Optimization (PSO) algorithm and Support Vector Machine (SVM). We combine it with Learning Automata in order to make it more efficient. This helps to select better features using the reward and penalty system of automata. To evaluate the efficiency of the proposed method, we compare it with a method which selects features based on Genetic Algorithm over the Reuters-21578 dataset. The simulation results show that our proposed algorithm works more efficiently

A Cost-Aware Mechanism for Optimized Resource Provisioning in Cloud Computing

Due to the recent wide use of computational resources in cloud computing, new resource provisioning challenges have been emerged. Resource provisioning techniques must keep total costs to a minimum while meeting the requirements of the requests. According to widely usage of cloud services, it seems more challenging to develop effective schemes for provisioning services cost-effectively; we have proposed a novel learning based resource provisioning approach that achieves cost-reduction guarantees of demands. The contributions of our optimized resource provisioning (ORP) approach are as follows. Firstly, it is designed to provide a cost-effective method to efficiently handle the provisioning of requested applications; while most of the existing models allow only workflows in general which cares about the dependencies of the tasks, ORP performs based on services of which applications comprised and cares about their efficient provisioning totally. Secondly, it is a learning automata-based approach which selects the most proper resources for hosting each service of the demanded application; our approach considers both cost and service requirements together for deploying applications. Thirdly, a comprehensive evaluation is performed for three typical workloads: data-intensive, process-intensive and normal applications. The experimental results show that our method adapts most of the requirements efficiently, and furthermore the resulting performance meets our design goals

Thermal modeling and analysis of advanced 3D stacked structures

AbstractThe emerging three-dimensional integrated circuits (3D ICs) offer a promising solution to mitigate the barriers of interconnect scaling in modern systems. It also provides greater design flexibility by allowing heterogeneous integration. However, 3D technology exacerbates the on-chip thermal issues and increases packaging and cooling costs. In this work, a 3D thermal model of a stacked system is developed and thermal analysis is performed in order to analyze different workload conditions using finite element simulations. The steady-state heat transfer analysis on the 3D stacked structure has been performed in order to analyze the effect of variation of die power consumption, with and without hotspots, on temperature in different layers of the stack has been analyzed. We have also investigated the effect of the interaction of hotspots has on peak temperature

Dynamic Pricing of Applications in Cloud Marketplaces using Game Theory

The competitive nature of Cloud marketplaces as new concerns in delivery of services makes the pricing policies a crucial task for firms. so that, pricing strategies has recently attracted many researchers. Since game theory can handle such competing well this concern is addressed by designing a normal form game between providers in current research. A committee is considered in which providers register for improving their competition based pricing policies. The functionality of game theory is applied to design dynamic pricing policies. The usage of the committee makes the game a complete information one, in which each player is aware of every others payoff functions. The players enhance their pricing policies to maximize their profits. The contribution of this paper is the quantitative modeling of Cloud marketplaces in form of a game to provide novel dynamic pricing strategies; the model is validated by proving the existence and the uniqueness of Nash equilibrium of the game

Effect of Adverse Weather Conditions on Vehicle Braking Distance of Highways

The effect of adverse weather conditions on the safety of vehicles moving on different types of roads and measuring its margin of safety have always been a major research issue of highways. Determining the exact value of friction coefficient between the wheels of the vehicle and the surface of the pavement (usually Asphalt Concrete) in different weather conditions is assumed as a major factor in design process. An appropriate method is analyzing the dynamic motion of the vehicle and its interactions with geometrical elements of road using dynamic simulation of vehicles. In this paper the effect of changes of friction coefficient caused by the weather conditions on the dynamic responses of three types of vehicles: including Sedan, Bus, and Truck based on the results of Adams/car Simulator are investigated. The studies conducted on this issue for different weather conditions suggest values ranging from 0.04 to 1.25. The results obtained from simulation based on Adams/car represent that the friction coefficient in values of 0.9, 0.8, 0.7, 0.6 do not effect on braking distance significantly and it is possible to attribute them all to dry weather condition. However, as it was anticipated the values of 0.5, 0.4, 0.28 and 0.18 have significant differences in braking distance. Hence, the values of 0.5, 0.4, 0.28 and 0.18 can be attributed to wet, rainy, snowy and icy conditions respectively

Alteration of hepatocellular antioxidant gene expression pattern and biomarkers of oxidative damage in diazinon-induced acute toxicity in Wistar rat

In the present survey, the plasma level of diazinon after acute exposure was measured by HPLC method at a time-course manner. In addition, the impact of diazinon on the expression of the key genes responsible for hepatocellular antioxidative defense, including PON1, GPx and CAT were investigated. The increase in oxidative damages in treated rats was determined by measuring LPO, protein carbonyl content and total antioxidant power in plasma. After administration of 85 mg/kg diazinon in ten groups of male Wistar rats at different time points between 0-24 hours, the activity of AChE enzyme was inhibited to about 77.94 %. Significant increases in carbonyl groups and LPO after 0.75 and 1 hours were also observed while the plasma antioxidant power was significantly decreased. Despite the dramatic reduction of GPX and PON1 gene expression, CAT gene was significantly upregulated in mRNA level by 1.1 fold after 4 hours and 1.5-fold after 24 hours due to diazinon exposure, compared to control group. Furthermore, no significant changes in diazinon plasma levels were found after 4 hours in the treated rats. The limits of detection and quantification were 137.42 and 416.52 ng/mL, respectively. The average percentage recoveries from plasma were between 90.62 % and 95.72 %. In conclusion, acute exposure to diazinon increased oxidative stress markers in a time-dependent manner and the changes were consistent with effects on hepatic antioxidant gene expression pattern. The effect of diazinon even as a non-lethal dose was induced on the gene expression of antioxidant enzymes. The change in antioxidant defense system occurs prior to diazinon plasma peak time. These results provide biochemical and molecular evidence supporting potential acute toxicity of diazinon and is beneficial in the evaluation of acute toxicity of other organophosphorus pesticides as well

Evaluating Kyphosis and Lordosis in Students by Using a Flexible Ruler and Their Relationship with Severity and Frequency of Thoracic and Lumbar Pain

Study DesignA cross-sectional, descriptive study.PurposeThis study aimed to investigate the relationship between kyphosis and lordosis measured by using a flexible ruler and musculoskeletal pain in students of Hamadan University of Medical Sciences.Overview of LiteratureThe spine supports the body during different activities by maintaining appropriate body alignment and posture. Normal alignment of the spine depends on its structural, muscular, bony, and articular performance.MethodsTwo hundred forty-one students participated in this study. A single examiner evaluated the angles of lumbar lordosis and thoracic kyphosis by using a flexible ruler. To determine the severity and frequency of pain in low-back and inter-scapular regions, a tailor-made questionnaire with visual analog scale was used. Finally, using the Kendall correlation coefficient, the data were statistically analyzed.ResultsThe mean value of lumbar lordosis was 34.46°±12.61° in female students and 22.46°±9.9° in male students. The mean value of lumbar lordosis significantly differed between female and male students (p<0.001). However, there was no difference in the level of the thoracic curve (p=0.288). Relationship between kyphosis measured by using a flexible ruler and inter-scapular pain in male and female students was not significant (p=0.946). However, the relationship between lumbar lordosis and low back pain was statistically significant (p=0.006). Also, no significant relationship was observed between abnormal kyphosis and frequency of inter-scapular pain, and between lumbar lordosis and low back pain.ConclusionsLumbar lordosis contributes to low back pain. The causes of musculoskeletal pain could be muscle imbalance and muscle and ligament strain