Adaptive Routing Approaches for Networked Many-Core Systems

Through advances in technology, System-on-Chip design is moving towards integrating tens to hundreds of intellectual property blocks into a single chip. In such a many-core system, on-chip communication becomes a performance bottleneck for high performance designs. Network-on-Chip (NoC) has emerged as a viable solution for the communication challenges in highly complex chips. The NoC architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication challenges such as wiring complexity, communication latency, and bandwidth. Furthermore, the combined benefits of 3D IC and NoC schemes provide the possibility of designing a high performance system in a limited chip area. The major advantages of 3D NoCs are the considerable reductions in average latency and power consumption. There are several factors degrading the performance of NoCs. In this thesis, we investigate three main performance-limiting factors: network congestion, faults, and the lack of efficient multicast support. We address these issues by the means of routing algorithms. Congestion of data packets may lead to increased network latency and power consumption. Thus, we propose three different approaches for alleviating such congestion in the network. The first approach is based on measuring the congestion information in different regions of the network, distributing the information over the network, and utilizing this information when making a routing decision. The second approach employs a learning method to dynamically find the less congested routes according to the underlying traffic. The third approach is based on a fuzzy-logic technique to perform better routing decisions when traffic information of different routes is available. Faults affect performance significantly, as then packets should take longer paths in order to be routed around the faults, which in turn increases congestion around the faulty regions. We propose four methods to tolerate faults at the link and switch level by using only the shortest paths as long as such path exists. The unique characteristic among these methods is the toleration of faults while also maintaining the performance of NoCs. To the best of our knowledge, these algorithms are the first approaches to bypassing faults prior to reaching them while avoiding unnecessary misrouting of packets. Current implementations of multicast communication result in a significant performance loss for unicast traffic. This is due to the fact that the routing rules of multicast packets limit the adaptivity of unicast packets. We present an approach in which both unicast and multicast packets can be efficiently routed within the network. While suggesting a more efficient multicast support, the proposed approach does not affect the performance of unicast routing at all. In addition, in order to reduce the overall path length of multicast packets, we present several partitioning methods along with their analytical models for latency measurement. This approach is discussed in the context of 3D mesh networks.

On the development of an unstructured grid solver for inert and reactive high speed flow simulations

An unstructured grid Euler solver for reactive compressible flow applications is presented. The method is implemented in a cell centered, finite volume context for unstructured triangular grids. Three different schemes for spatial discretization are implemented and analyzed. Time march is implemented in a time-split fashion with independent integrators for the flow and chemistry equations. The capability implemented is tested for inert flows in a hypersonic inlet and for inert and reactive supersonic flows over a 2-D wedge. The results of the different schemes are compared with each other and with independent calculations using a structured grid code. The strengths and the possible weaknesses of the proposed methods are discussed.

Dynamics of coherent vortices in mixing layers using direct numerical and large-eddy simulations

Coherent vortices in turbulent mixing layers are investigated by means of Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES). Subgrid-scale models defined in spectral and physical spaces are reviewed. The new "spectral-dynamic viscosity model", that allows to account for non-developed turbulence in the subgrid-scales, is discussed. Pseudo-spectral methods, combined with sixth-order compact finite differences schemes (when periodic boundary conditions cannot be established), are used to solve the Navier- Stokes equations. Simulations in temporal and spatial mixing layers show two types of pairing of primary Kelvin-Helmholtz (KH) vortices depending on initial conditions (or upstream conditions): quasi-2D and helical pairings. In both cases, secondary streamwise vortices are stretched in between the KH vortices at an angle of 45° with the horizontal plane. These streamwise vortices are not only identified in the early transitional stage of the mixing layer but also in self-similar turbulence conditions. The Re dependence of the "diameter" of these vortices is analyzed. Results obtained in spatial growing mixing layers show some evidences of pairing of secondary vortices; after a pairing of the primary Kelvin-Helmholtz (KH) vortices, the streamwise vortices are less numerous and their diameter has increased than before the pairing of KH vortices.

Numerical study on mixed convection in a horizontal flow past a square porous cavity using UNIFAES scheme

Mixed convection on the flow past a heated length and past a porous cavity located in a horizontal wall bounding a saturated porous medium is numerically simulated. The cavity is heated from below. The steady-state regime is studied for several intensities of the buoyancy effects due to temperature variations. The influences of Péclet and Rayleigh numbers on the flow pattern and the temperature distributions are examined. Local and global Nusselt numbers are reported for the heated surface. The convective-diffusive fluxes at the volume boundaries are represented using the UNIFAES, Unified Finite Approach Exponential-type Scheme, with the Power-Law approximation to reduce the computing time. The conditions established by Rivas for the quadratic order of accuracy of the central differencing to be maintained in irregular grids are shown to be extensible to other quadratic schemes, including UNIFAES, so that accuracy estimates could be obtained.

A Well Stated Time Domain Integral Representation for Elastodynamic Analysis and Applications

This article discusses three possible ways to derive time domain boundary integral representations for elastodynamics. This discussion points out possible difficulties found when using those formulations to deal with practical applications. The discussion points out recommendations to select the convenient integral representation to deal with elastodynamic problems and opens the possibility of deriving simplified schemes. The proper way to take into account initial conditions applied to the body is an interesting topict shown. It illustrates the main differences between the discussed boundary integral representation expressions, their singularities and possible numerical problems. The correct way to use collocation points outside the analyzed domain is carefully described. Some applications are shown at the end of the paper, in order to demonstrate the capabilities of the technique when properly used.

Substitution-Newton-Raphson method applied to the modeling of a vapour compression refrigeration system using different representations of the thermodynamic properties of R-134a

This paper gives a detailed presentation of the Substitution-Newton-Raphson method, suitable for large sparse non-linear systems. It combines the Successive Substitution method and the Newton-Raphson method in such way as to take the best advantages of both, keeping the convergence features of the Newton-Raphson with the low requirements of memory and time of the Successive Substitution schemes. The large system is solved employing few effective variables, using the greatest possible part of the model equations in substitution fashion to fix the remaining variables, but maintaining the convergence characteristics of the Newton-Raphson. The methodology is exemplified through a simple algebraic system, and applied to a simple thermodynamic, mechanical and heat transfer modeling of a single-stage vapor compression refrigeration system. Three distinct approaches for reproducing the thermodynamic properties of the refrigerant R-134a are compared: the linear interpolation from tabulated data, the use of polynomial fitted curves and the use of functions derived from the Helmholtz free energy.

Communication Solutions for LVDC Island Networks

Production and generation of electrical power is evolving to more environmental friendly technologies and schemes. Pushed by the increasing cost of fossil fuels, the operational costs of producing electrical power with fossil fuels and the effect in the environment, like pollution and global warming, renewable energy sources gain con-stant impulse into the global energy economy. In consequence, the introduction of distributed energy sources has brought a new complexity to the electrical networks. In the new concept of smart grids and decen-tralized power generation; control, protection and measurement are also distributed and requiring, among other things, a new scheme of communication to operate with each other in balance and improve performance. In this research, an analysis of different communication technologies (power line communication, Ethernet over unshielded twisted pair (UTP), optic fiber, Wi-Fi, Wi-MAX, and Long Term Evolution) and their respective characteristics will be carried out. With the objective of pointing out strengths and weaknesses from different points of view (technical, economical, deployment, etc.) to establish a richer context on which a decision for communication approach can be done depending on the specific application scenario of a new smart grid deployment. As a result, a description of possible optimal deployment solutions for communication will be shown considering different options for technologies, and a mention of different important considerations to be taken into account will be made for some of the possible network implementation scenarios.

Numerical Simulation of Stochastic Di erential Equations

Stochastic differential equation (SDE) is a differential equation in which some of the terms and its solution are stochastic processes. SDEs play a central role in modeling physical systems like finance, Biology, Engineering, to mention some. In modeling process, the computation of the trajectories (sample paths) of solutions to SDEs is very important. However, the exact solution to a SDE is generally difficult to obtain due to non-differentiability character of realizations of the Brownian motion. There exist approximation methods of solutions of SDE. The solutions will be continuous stochastic processes that represent diffusive dynamics, a common modeling assumption for financial, Biology, physical, environmental systems. This Masters' thesis is an introduction and survey of numerical solution methods for stochastic differential equations. Standard numerical methods, local linearization methods and filtering methods are well described. We compute the root mean square errors for each method from which we propose a better numerical scheme. Stochastic differential equations can be formulated from a given ordinary differential equations. In this thesis, we describe two kind of formulations: parametric and non-parametric techniques. The formulation is based on epidemiological SEIR model. This methods have a tendency of increasing parameters in the constructed SDEs, hence, it requires more data. We compare the two techniques numerically.

Commercialization of Modern Renewable Energy

The threat of global warming and its consequences are widely recognized, and the question of how to proceed with the long transition towards fossil fuel -neutral economies concerns many nations and people. At the same time the world’s primary energy use is predicted to increase significantly during the next decades as a result of global population and welfare increase. Improved energy efficiency and increased use of renewable energy sources in the world’s energy mix play important roles in the future energy production and consumption. The objective of this thesis is to study how novel renewable energy technologies, such as distributed small-scale bio-fueled combined heat and power production and wind power technologies could be commercialized efficiently. A wide array of attributes may contribute to the diffusion of new products. In general, the bioenergy and wind power technologies are in emerging phases, and the diffusion stage varies from country to country. The effects of firms’ technology choices, collaboration and alliances are studied in this thesis. Furthermore, the roles of national energy infrastructure and energy support schemes in the commercialization of new renewable energy products are explored. The empirical data is based on energy expert interviews, financial and patent data, and literature reviews of different case studies. The thesis comprises two parts. The first part provides an overview of the study, and the second part includes six research publications. The results reveal that small-scale bio-fueled combined heat and power production and wind power technologies are still in emerging phases in their life cycles, and energy support schemes are crucial in the market diffusion. The study contributes to earlier findings in the literature and industry by confirming that adequate energy policies and energy infrastructure are fundamental in the commercialization of novel renewable energy technologies. Firm-specific issues, including business relationships and new business models, and market-related issues will have a more significant role in the market penetration in the future, when the technologies mature and become competitive without political support schemes.

Detection of Illicit Drugs and Drug Precursors with Cantilever-Enhanced Photoacoustic Spectroscopy

In this study, cantilever-enhanced photoacoustic spectroscopy (CEPAS) was applied in different drug detection schemes. The study was divided into two different applications: trace detection of vaporized drugs and drug precursors in the gas-phase, and detection of cocaine abuse in hair. The main focus, however, was the study of hair samples. In the gas-phase, methyl benzoate, a hydrolysis product of cocaine hydrochloride, and benzyl methyl ketone (BMK), a precursor of amphetamine and methamphetamine were investigated. In the solid-phase, hair samples from cocaine overdose patients were measured and compared to a drug-free reference group. As hair consists mostly of long fibrous proteins generally called keratin, proteins from fingernails and saliva were also studied for comparison. Different measurement setups were applied in this study. Gas measurements were carried out using quantum cascade lasers (QLC) as a source in the photoacoustic detection. Also, an external cavity (EC) design was used for a broader tuning range. Detection limits of 3.4 particles per billion (ppb) for methyl benzoate and 26 ppb for BMK in 0.9 s were achieved with the EC-QCL PAS setup. The achieved detection limits are sufficient for realistic drug detection applications. The measurements from drug overdose patients were carried out using Fourier transform infrared (FTIR) PAS. The drug-containing hair samples and drug-free samples were both measured with the FTIR-PAS setup, and the measured spectra were analyzed statistically with principal component analysis (PCA). The two groups were separated by their spectra with PCA and proper spectral pre-processing. To improve the method, ECQCL measurements of the hair samples, and studies using photoacoustic microsampling techniques, were performed. High quality, high-resolution spectra with a broad tuning range were recorded from a single hair fiber. This broad tuning range of an EC-QCL has not previously been used in the photoacoustic spectroscopy of solids. However, no drug detection studies were performed with the EC-QCL solid-phase setup.

Forest cover and its change in Unguja Island, Zanzibar

Tropical forests are sources of many ecosystem services, but these forests are vanishing rapidly. The situation is severe in Sub-Saharan Africa and especially in Tanzania. The causes of change are multidimensional and strongly interdependent, and only understanding them comprehensively helps to change the ongoing unsustainable trends of forest decline. Ongoing forest changes, their spatiality and connection to humans and environment can be studied with the methods of Land Change Science. The knowledge produced with these methods helps to make arguments about the actors, actions and causes that are behind the forest decline. In this study of Unguja Island in Zanzibar the focus is in the current forest cover and its changes between 1996 and 2009. The cover and changes are measured with often used remote sensing methods of automated land cover classification and post-classification comparison from medium resolution satellite images. Kernel Density Estimation is used to determine the clusters of change, sub-area –analysis provides information about the differences between regions, while distance and regression analyses connect changes to environmental factors. These analyses do not only explain the happened changes, but also allow building quantitative and spatial future scenarios. Similar study has not been made for Unguja and therefore it provides new information, which is beneficial for the whole society. The results show that 572 km2 of Unguja is still forested, but 0,82–1,19% of these forests are disappearing annually. Besides deforestation also vertical degradation and spatial changes are significant problems. Deforestation is most severe in the communal indigenous forests, but also agroforests are decreasing. Spatially deforestation concentrates to the areas close to the coastline, population and Zanzibar Town. Biophysical factors on the other hand do not seem to influence the ongoing deforestation process. If the current trend continues there should be approximately 485 km2 of forests remaining in 2025. Solutions to these deforestation problems should be looked from sustainable land use management, surveying and protection of the forests in risk areas and spatially targeted self-sustainable tree planting schemes.

Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

The assembly and maintenance of the International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. The VV is made of stainless steel, which has poor machinability and tends to work harden very rapidly, and all the machining operations need to be carried out from inside of the ITER VV. A general industrial robot cannot be used due to its poor stiffness in the heavy duty machining process, and this will cause many problems, such as poor surface quality, tool damage, low accuracy. Therefore, one of the most suitable options should be a light weight mobile robot which is able to move around inside of the VV and perform different machining tasks by replacing different cutting tools. Reducing the mass of the robot manipulators offers many advantages: reduced material costs, reduced power consumption, the possibility of using smaller actuators, and a higher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight robot is more flexible, which makes it more difficult to control. To achieve good machining surface quality, the tracking of the end effector must be accurate, and an accurate model for a more flexible robot must be constructed. This thesis studies the dynamics and control of a 10 degree-of-freedom (DOF) redundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel mechanisms) hydraulically driven with flexible rods under the influence of machining forces. Firstly, the flexibility of the bodies is described using the floating frame of reference method (FFRF). A finite element model (FEM) provided the Craig-Bampton (CB) modes needed for the FFRF. A dynamic model of the system of six closed loop mechanisms was assembled using the constrained Lagrange equations and the Lagrange multiplier method. Subsequently, the reaction forces between the parallel and serial parts were used to study the dynamics of the serial robot. A PID control based on position predictions was implemented independently to control the hydraulic cylinders of the robot. Secondly, in machining, to achieve greater end effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. This thesis investigates the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID self-tuning controller composed of the conventional PID control and with fuzzy logic, and (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel mechanism based on rod length predictions. The serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should be controlled to hold the hexa-element. Thirdly, a finite element approach of multibody systems using the Special Euclidean group SE(3) framework is presented for a parallel mechanism with flexible piston rods under the influence of machining forces. The flexibility of the bodies is described using the nonlinear interpolation method with an exponential map. The equations of motion take the form of a differential algebraic equation on a Lie group, which is solved using a Lie group time integration scheme. The method relies on the local description of motions, so that it provides a singularity-free formulation, and no parameterization of the nodal variables needs to be introduced. The flexible slider constraint is formulated using a Lie group and used for modeling a flexible rod sliding inside a cylinder. The dynamic model of the system of six closed loop mechanisms was assembled using Hamilton’s principle and the Lagrange multiplier method. A linearized hydraulic control system based on rod length predictions was implemented independently to control the hydraulic cylinders. Consequently, the results of the simulations demonstrating the behavior of the robot machine are presented for each case study. In conclusion, this thesis studies the dynamic analysis of a special hybrid (serialparallel) robot for the above-mentioned special task involving the ITER and investigates different control algorithms that can significantly improve machining performance. These analyses and results provide valuable insight into the design and control of the parallel robot with flexible rods.

Sunflower response to repeated foliar applications of Paclobutrazol

Paclobutrazol (PBZ), a well-known growth retardant of the triazole family, is mostly used for controlling plant size and growth, resulting in more desirable compact plants for floricultural purposes; however, limited experimental data are available for use of PBZ in field sunflower. The objective of this study was to evaluate the effect of repeated foliar applications of PBZ at rates of 50 + 50 g ha-1(double application) and 50 + 50 + 50 g ha-1 (triple application) on sunflower morphology and productivity. PBZ applications corresponded to growth stages of four to five, five to six, and six to eight true leaves of sunflower plants, respectively. The double foliar application of PBZ reduced sunflower plant height at maturity by 4.4% (or by 11.7 cm). The triple foliar application of PBZ reduced sunflower plant height at maturity by 14.4% (or by 49.2 cm). However, PBZ either in the double or the triple application reduced achene yield per plant by 25.6% and 22.5% and the 100-achene weight by 11.4% and 25.0%, respectively, compared with the non-treated control. Overall, the repeated foliar applications of PBZ at the rates tested in this study, apart from providing a reduction of sunflower plant height, had major adverse effects on achene yield and weight. Thus, different application schemes of PBZ or perhaps different growth regulators should be investigated to control plant height in sunflower.

Integrating CRIS and repository – an overview of the situation in Finland and in three other Nordic countries

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A DNS Bases Approach To Electronic Persistance, or "If Your Pants Fit, Why Use Suspenders?"

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014