Eddie Wadbro

Megapixel Topology Optimization on a Graphics Processing Unit

We show how the computational power and programmability of modern graphics processing units (GPUs) can be used to efficiently solve large-scale pixel-based material distribution problems using a gradient-based optimality criterion method. To illustrate the principle, a so-called topology optimization problem that results in a constrained nonlinear programming problem with over 4 million decision variables is solved on a commodity GPU.

Topology Optimization of Metallic Antennas

We introduce an approach to carry out layout optimization of metallic antenna parts. An optimization technique first developed for the optimization of load-bearing elastic structures is adapted for the purpose of metallic antenna design. The local conductivity values in a given region are used as design variables and are iteratively updated by a gradient-based optimization algorithm. Given a set of time-domain signals from exterior sources, the design objective is here to maximize the energy received by the antenna and transmitted to a coaxial cable. The optimization proceeds through a sequence of coarsely-defined lossy designs with successively increasing details and less losses as the iterations proceed. The objective function gradient is derived based on the FDTD discretization of Maxwells equations and is expressed in terms of field solutions of the original antenna problem and an adjoint field problem. The same FDTD code, but with different wave sources, is used for both the original antenna problem and the adjoint problem. For any number of design variables, the gradient is evaluated on the basis of only two FDTD simulations, one for the original antenna problem and another for the adjoint field problem. We demonstrate the capability of the method by optimizing the radiating patch of both UWB monopole and microstrip antennas. The UWB monopole is designed to radiate over a wide frequency band 1-10 GHz, while the microstrip patch is designed for single and dual frequency band operation. In these examples, there are more than 20,000 design variables, and the algorithm typically converges in less than 150 iterations. The optimization results show a promising use of the proposed approach as a general method for conceptual design of near-resonance metallic antennas.

Shape and topology optimization of an acoustic horn-lens combination

Using gradient-based optimization combined with numerical solutions of the Helmholtz equation, we design an acoustic device with high transmission efficiency and even directivity throughout a two-octave-wide frequency range. The device consists of a horn, whose flare is subject to boundary shape optimization, together with an area in front of the horn, where solid material arbitrarily can be distributed using topology optimization techniques, effectively creating an acoustic lens.

Continuous Datacenter Consolidation

Efficient mapping of Virtual Machines~(VMs) onto physical servers is a key problem for cloud infrastructure providers as hardware utilization directly impacts profit. Today, this mapping is commonly only performed when new VMs are created, but as VM workloads fluctuate and server availability varies, any initial mapping is bound to become suboptimal over time. We introduce a set of heuristic methods for continuous optimization of the VM-to-server mapping based on combinations of fundamental management actions, namely suspending and resuming physical machines, migrating VMs, and suspending and resuming VMs. By using these methods, cloud infrastructure providers can continuously optimize their server resources regardless of the predictability of the workload. To verify that our approach is applicable in real-world scenarios, we build a proof-of-concept datacenter management system that implements the proposed algorithms. The feasibility of our approach is evaluated through a combination of simulations and real experiments where our system provisions a workload of benchmark applications. Our results indicate that the proposed algorithms are feasible, that the combined management approach achieves the best results, and that the VM suspend and resume mechanism has the largest impact on provider profit.

Dynamic application placement in the Mobile Cloud Network

To meet the challenges of consistent performance, low communication latency, and a high degree of user mobility, cloud and Telecom infrastructure vendors and operators foresee a Mobile Cloud Network that incorporates public cloud infrastructures with cloud augmented Telecom nodes in forthcoming mobile access networks. A Mobile Cloud Network is composed of distributed cost- and capacity-heterogeneous resources that host applications that in turn are subject to a spatially and quantitatively rapidly changing demand. Such an infrastructure requires a holistic management approach that ensures that the resident applications performance requirements are met while sustainably supported by the underlying infrastructure. The contribution of this paper is three-fold. Firstly, this paper contributes with a model that captures the cost- and capacity-heterogeneity of a Mobile Cloud Network infrastructure. The model bridges the Mobile Edge Computing and Distributed Cloud paradigms by modelling multiple tiers of resources across the network and serves not just mobile devices but any client beyond and within the network. A set of resource management challenges is presented based on this model. Secondly, an algorithm that holistically and optimally solves these challenges is proposed. The algorithm is formulated as an application placement method that incorporates aspects of network link capacity, desired user latency and user mobility, as well as data centre resource utilisation and server provisioning costs. Thirdly, to address scalability, a tractable locally optimal algorithm is presented. The evaluation demonstrates that the placement algorithm significantly improves latency, resource utilisation skewness while minimising the operational cost of the system. Additionally, the proposed model and evaluation method demonstrate the viability of dynamic resource management of the Mobile Cloud Network and the need for accommodating rapidly mobile demand in a holistic manner. Proposes a holistic cost-optimal management approach for the forthcoming Mobile Cloud Network.The proposed method shows significant improvements in aggregate system cost and resource utilisation skewness, and proves to be very capable at accommodating user mobility.The evaluations reveal that high cost of user mobility and the amount of coordinated effort is required to accommodate it.The proposed method provides an upper bound to which we can contrast more tractable distributed solutions.

DieHard: Reliable Scheduling to Survive Correlated Failures in Cloud Data Centers

In large scale data centers, a single fault can lead to correlated failures of several physical machines and the tasks running on them, simultaneously. Such correlated failures can severely damage the reliability of a service or a job. This paper models the impact of stochastic and correlated failures on job reliability in a data center. We focus on correlated failures caused by power outages or failures of network components, on jobs running multiple replicas of identical tasks. We present a statistical reliability model and an approximation technique for computing a jobs reliability in the presence of correlated failures. In addition, we address the problem of scheduling a job with reliability constraints. We formulate the scheduling problem as an optimization problem, with the aim being to achieve the desired reliability with the minimum number of extra tasks. We present a scheduling algorithm that approximates the minimum number of required tasks and a placement to achieve a desired job reliability. We study the efficiency of our algorithm using an analytical approach and by simulating a cluster with different failure sources and reliabilities. The results show that the algorithm can effectively approximate the minimum number of extra tasks required to achieve the jobs reliability.

Topology optimization of wave transducers

We apply topology optimization in order to design an acoustic horn that radiates sound as efficiently as possible. At the same time, we wish to monitor and control also the directivity properties of the horn. Topology optimization provides a rational approach to difficult design problems, such as finding the complex shape required for efficient transmission of sound at frequencies that are too low to efficiently transmit in a short straight horn.

Patch and ground plane design of microstrip antennas by material distribution topologly optimization

We use a gradient-based material distribution approach to design conductive parts of microstrip antennas in an efficient way. The approach is based on solutions of the 3D Maxwells equation compute ...

Microwave Tomography Using Topology Optimization Techniques

Microwave tomography is a technique in which microwaves illuminate a specimen, and measurements of the scattered electrical field are used to determine and depict the specimens dielectric and conductive properties. This article presents a new method to perform the reconstruction. The reconstruction method is illustrated by assuming time harmonic scattering in two space dimensions in a setup tailored for medical applications. We prove that the resulting constrained nonlinear least-squares problem admits a solution. The governing Helmholtz equation is discretized by using the finite-element method, and the dielectric properties are allowed to attain different values at each element within a given region. The reconstruction algorithm uses methodologies borrowed from topology optimization of linearly elastic structures. Numerical examples illustrate the reconstruction method in a parameter range typical for human tissue and for the challenging case where the size of the object is in the same order as the wavelength. A reasonable estimate of the dielectric properties is obtained by using one observation per 20 unknowns when the permittivity is allowed to vary continuously within a given interval. Using a priori information that the permittivity attains only certain values results in a good estimate and a sharp image. As opposed to topology optimization for structures, there is no indication of mesh dependency and checkerboarding when forcing the permittivity to attain discrete values.

Topology Optimization of Planar Antennas for Wideband Near-Field Coupling

We present an approach to design from scratch planar microwave antennas for the purpose of ultra-wideband (UWB) near-field sensing. Up to about 120 000 design variables associated with square grids on planar substrates are subject to design, and a numerical optimization algorithm decides, after around 200 iterations, for each edge in the grid whether it should consist of metal or a dielectric. The antenna layouts produced with this approach show UWB impedance matching properties and near-field coupling coefficients that are Hat over a much wider frequency range than a standard UWB antenna. The properties of the optimized antennas are successfully cross-verified with a commercial software and, for one of the designs, also validated experimentally. We demonstrate that an antenna optimized in this way shows a high sensitivity when used for near-field detection of a phantom with dielectric properties representative of muscle tissue.