Pipelined Multiprocessor System-on-Chip for Multimedia

System-level dynamic power management (DPM) schemes in Multiprocessor System on Chips (MPSoCs) exploit the idleness of processors to reduce the energy consumption by putting idle processors to low-power states. In the presence of multiple low-power states, the challenge is to predict the duration of the idle period with high accuracy so that the most beneficial power state can be selected for the idle processor. In this work, we propose a novel dynamic power management scheme for adaptive pipelined MPSoCs, suitable for multimedia applications. We leverage application knowledge in the form of future workload prediction to forecast the duration of idle periods. The predicted duration is then used to select an appropriate power state for the idle processor. We proposed five heuristics as part of the DPM and compared their effectiveness using an MPSoC implementation of the H.264 video encoder supporting HD720p at 30 fps. The results show that one of the application prediction based heuristic (MAMAPBH) predicted the most beneficial power states for idle processors with less than 3% error when compared to an optimal solution. In terms of energy savings, MAMAPBH was always within 1% of the energy savings of the optimal solution. When compared with a naive approach (where only one of the possible power states is used for all the idle processors), MAMAPBH achieved up to 40% more energy savings with only 0.5% degradation in throughput. These results signify the importance of leveraging application knowledge at system-level for dynamic power management schemes.

Loss of steam quality and energy in steam injection wells is a key component in the design of steam-based thermal operations. These operations are increasingly employing more sophisticated wells that have longer trajectories with multiple control points. Reservoir simulation of thermal fields requires high accuracy in thermal boundary conditions for all wells, and conductive heat loss often plays a large role in overall energy conservation. Thermal injection wells are usually modelled only in the reservoir where injection enthalpy and steam quality at the bottom hole depth are estimated. In this paper, an examination is made of the benefits of modelling conductive heat and quality loss through the upper formation as part of the overall field simulation. A comparison is made between the use of analytic models for heat and quality loss through the overburden based on work by Ramey and Satter, and a multisegment thermal well model that is segmented from the surface through the overburden and to the top of the oil-bearing formation. The analytic models of heat and steam quality loss are based on steady-state wellbore flow and conductive heat loss to the overburden. A more detailed representation of wellbore physics and control is available with the multi-segmented steam injection well model, including conductive heat transfer between the wellbore tubular and overburden or reservoir, a user-specified nodal resolution, a multiphase flow model that includes unequal phase flow rates of steam and condensate, the ability to correctly model the phase change of steam vapour to condensate as it flows downward from the surface, and an implicit coupling to the reservoir. Limitations of the analytic and segmented models are discussed including accuracy differences and instances when one or the other models may not be appropriate.

Network-on-Chip (NoC)-based multiprocessor system-on-chips (MPSoCs) are becoming the de-facto computing platform for computationally intensive real-time applications in the embedded systems due to their high performance, exceptional quality-of-service (QoS) and energy efficiency over superscalar uniprocessor architectures. Energy saving is important in the embedded system because it reduces the operating cost while prolongs lifetime and improves the reliability of the system. In this paper, contention-aware energy efficient static mapping using NoC-based heterogeneous MPSoC for real-time tasks with an individual deadline and precedence constraints is investigated. Unlike other schemes task ordering, mapping, and voltage assignment are performed in an integrated manner to minimize the processing energy while explicitly reduce contention between the communications and communication energy. Furthermore, both dynamic voltage and frequency scaling and dynamic power management are used for energy consumption optimization. The developed contention-aware integrated task mapping and voltage assignment (CITM-VA) static energy management scheme performs tasks ordering using earliest latest finish time first (ELFTF) strategy that assigns priorities to the tasks having shorter latest finish time (LFT) over the tasks with longer LFT. It remaps every task to a processor and/or discrete voltage level that reduces processing energy consumption. Similarly, the communication energy is minimized by assigning discrete voltage levels to the NoC links. Further, total energy efficiency is achieved by putting the processor into a low-power state when feasible. Moreover, this approach resolves the contention between communications that traverse the same link by allocating links to communications with higher priority. The results obtained through extensive simulations of real-world benchmarks demonstrate that CITM-VA approach outperforms state-of-the-art technique and achieves an average ~30% total energy improvement. Additionally, it maintains high QoS and robustness for real-time applications.

The aim of this contribution is to compare two hybrid analytical models for the study of a series hybrid excited synchronous structure performance. Hybrid excited synchronous machines, due to their advantageous characteristics and performance, are good candidates in a large variety of applications. The goal of this study is to address two problems related to the use of analytical models for design and analysis purposes. The first is to find methods helping to overcome numerical problems met when analytical models based on the formal resolution of Maxwell's equations are used for the analysis and design of series double excitation machines. The second goal is to find methods allowing speeding up of the pre-design and analysis of series double excitation machines.

The majority of applications, ranging from the low complexity to very multifaceted entities requiring dedicated hardware accelerators, are very well suited for Multiprocessor Systems-on-Chips (MPSoCs). It is critical to understand the general characteristics of a given embedded application: its behavior and its requirements in terms of MPSoC resources. This paper presents a complete method to study the important aspect of memory characteristic of an application. This method spans the theoretical, architecture-independent memory characterization to the quasi optimal static memory allocation of an application on a real shared-memory MPSoCs. The application is modeled as an Synchronous Dataflow (SDF) graph which is used to derive a Memory Exclusion Graph (MEG) essential for the analysis and allocation techniques. Practical considerations, such as cache coherence and memory broadcasting, are extensively treated. Memory footprint optimization is demonstrated using the example of a stereo matching algorithm from the computer vision domain. Experimental results show a reduction of the memory footprint by up to 43 % compared to a state-of-the-art minimization technique, a throughput improvement of 33 % over dynamic allocation, and the introduction of a tradeoff between multicore scheduling flexibility and memory footprint.

Wing weight estimation is one of the most important functions of the aircraft design process. For optimization process, the weight of the wing may have to be calculated thousands of time specially if it is a part of multidisciplinary optimization. For light weight UAV, four different models are used to calculate the weight of ribs, skin, spar and carry through structure respectively. Ingenuity is captured in weight estimation of spar and an iterative method to calculate weight of spar is presented. The weight of each individual item is added to get the approximate total weight of the wing. High level computational structural analysis is not possible in optimization phase due to computational time cost. The current weight estimation method is a part of high level multidisciplinary optimization thus robust results are desired. The wing weight estimation code is verified against analytical results and total weight is compared with an available light weight UAV. The results of wing comparison show good approximation and validate the weight estimation code. Thus the method proposed for wing weight estimation for light weight UAV is validated and the desired output of a robust method to calculate weight of the wing is achieved.

Next generation multiprocessor systems-on-chip (MPSoCs) are expected to contain numerous processing elements, interconnected via on-chip networks, executing real-time applications. It is anticipated that runtime optimization algorithms which dynamically adjust system parameters with the purpose of optimizing the system's operation, will be embedded in the system software and/or hardware. In this paper, we present a methodology for simulating and evaluating system-level optimization algorithms, demonstrated by the case of on-chip dynamic task allocation applied to generic MPSoC architectures. Through this methodology, we are able to show that dynamic, system-level bidding-based task allocation can improve system performance, when compared to a round robin allocation, in popular MPSoC applications.

This paper details the weight optimization of the electrical machine required for an Airborne Wind Turbine (AWT) system. Presented investigations include the analysis of the power-to-weight ratio versus efficiency limits, γ-η Pareto fronts, of radial and axial flux machine topologies, by making use of analytical models, describing the electromagnetic and thermal behaviour. A direct search method is employed rather than a cost function minimization algorithm, as the analytical models allow the evaluation of the whole design space in a computationally efficient manner. The results reveal that the best performance in this case is achieved with a radial flux machine with an internal rotor where the magnets are arranged in a Halbach configuration. Including the weight of electromagnetically inactive parts, such as bearings, shaft and housing, a power-to-weight ratio of γ ≈ 6.2 kW/kg (2.8 kW/lb), at an efficiency of η ≈ 96 %, and a rated speed of 3200 r/min is achieved.

When justifying the design parameters, it is necessary to carry out the analysis of the strain-strain state of individual elements of technological systems, which are sets of parts under contact interaction conditions. These problems are nonlinear, and the principle of superposition does not apply to them. For this reason, the amount of calculations increases dramatically. To overcome this drawback, methods and models for the rapid and precise study of the strain-strain state of complex objects, taking into account contact interaction are developed. The feature of the problem statement is that the solution of contact problems under certain conditions linearly depends on the load. The patterns of contact pressure distribution are determined. It is concentrated in the areas of constant shape and size. Only the scale of contact pressure distribution varies.This gives an opportunity to significantly accelerate design studies of die tooling while preserving the accuracy of numerical modeling of the stress-strain state.The developed approach involves a combination of advantages of numerical and analytical models and methods for analyzing the stress-strain state of elements of shearing dies, taking into account contact interaction. This concerns the possibility to solve problems for a system of complex-shaped contacting bodies, which is impossible with the use of analytical models. On the other hand, the possibility of scaling the solutions of these problems with the stamping force is substantiated, which is generally not performed for nonlinear contact problems. So, it is sufficient to solve the problem of determining the strain-strain state of elements of such a shearing die. For the other value of stamping force, the proportionality rule is applied. Thus, the efficiency of research sharply increases and high accuracy of the obtained results is ensured.

In this paper, the applicability of the Peukert equation and its generalizations were investigated for capacity evaluation of automotive-grade lithium-ion batteries. It is proved that the classical Peukert equation is applicable within the range of the discharge currents from 0.2Cn to 2Cn (Cn is the nominal battery capacity). As a rule, the operating currents of many automotive-grade lithium-ion batteries are exactly within this range of the discharge currents. That is why, successfully, the classical Peukert equation is used in many analytical models developed for these batteries. The generalized Peukert equation C = Cm/(1 + (i/i0)n) is applicable within the discharge currents range from zero to approximately 10Cn. All kinds of operating discharge currents (including both very small ones and powerful short-term bursts) fall into this discharge currents range. The modified Peukert equation C = Cm(1 − i/i1)/((1 − i/i1) + (i/i0)n) is applicable at any discharge currents. This equation takes into account the battery’s internal resistance and has the smallest error of experimental data approximation. That is why the discussed modified Peukert equation is most preferable for use in analytical models of automotive-grade lithium-ion batteries. The paper shows that all the parameters of the generalized Peukert equations have a clear electrochemical meaning in contrast to the classical Peukert equation, where all the parameters are just empirical constants.

In this proposed paper, a measurement based validation for a previously developed payload estimation method for excavators [1] is presented. The payload here refers to the weight exerted at the operating end (bucket) of the working attachment of an excavator due to the amount of material in the bucket. The proposed method employs an analytical approach, relying on calculating the payload as a function of the joint torques of the excavator working attachment. Since this approach requires the knowledge of the inertial parameters of the working attachment, a method to estimate these was proposed. The mass, center of mass and mass moment of inertia of each link are estimated recursively using simple motion trajectories of the working attachment. Once the inertial parameters are thus estimated, the payload can be estimated as a function of joint torques. Both these estimation methods were validated using measurements done on an 18 t hydraulic excavator. The paper discusses in detail the measurement runs performed for the validation, as well as the subsequent evaluation of the measurement data. Finally, the quality of the results is elaborated on, and suggestions for improvement of the accuracy and reproducibility of both estimation methods are presented.

Exploration of distributed shared memory architectures for NoC-based multiprocessors

Growing complexity of multiprocessor systems on chip (MP-SoC) requires future communication resources that can only be met by highly scalable architectures. Networks-on-Chip (NoCs) offer this scalability and other advantages like modularity, quality-of-service (QoS), possibly smaller area footprint and lower power dissipation. Although many papers describe the advantages of NoCs and describe techniques to apply NoCs on certain application domains, few have actually employed the complete design chain to make a netlist level implementation and area comparison (Steenhof et al., 2006) and (Angiolini et al., 2006). This paper describes the application of the AEligthereal NoC to an existing bus-based MP-SoC design and an area comparison with the original interconnects structure down to netlist level

This article discusses the methods and procedures for estimating the initial parameters of the Rice distribution known in the literature. The maximum likelihood method and the methods of different degrees’ moments are selected. A series of experiments on estimating the parameters from the obtained samples are performed by mathematical modeling of the methods and samples with given values of the initial parameters of the distribution. The advantage of the maximum likelihood method over the others is shown. A procedure for estimating the distribution shape parameter for small signal-to-noise ratios is developed.

Analytical and numerical hybrid capacity estimation method for multi-band elastic optical networks