Evaluation of performance analysis software for Linux computing cluster

Tietokonejärjestelmän osien ja ohjelmistojen suorituskykymittauksista saadaan tietoa,jota voidaan käyttää suorituskyvyn parantamiseen ja laitteistohankintojen päätöksen tukena. Tässä työssä tutustutaan suorituskyvyn mittaamiseen ja mittausohjelmiin eli ns. benchmark-ohjelmistoihin. Työssä etsittiin ja arvioitiin eri tyyppisiä vapaasti saatavilla olevia benchmark-ohjelmia, jotka soveltuvat Linux-laskentaklusterin suorituskyvynanalysointiin. Benchmarkit ryhmiteltiin ja arvioitiin testaamalla niiden ominaisuuksia Linux-klusterissa. Työssä käsitellään myös mittausten tekemisen ja rinnakkaislaskennan haasteita. Benchmarkkeja löytyi moneen tarkoitukseen ja ne osoittautuivat laadultaan ja laajuudeltaan vaihteleviksi. Niitä on myös koottu ohjelmistopaketeiksi, jotta laitteiston suorituskyvystä saisi laajemman kuvan kuin mitä yhdellä ohjelmalla on mahdollista saada. Olennaista on ymmärtää nopeus, jolla dataa saadaan siirretyä prosessorille keskusmuistista, levyjärjestelmistä ja toisista laskentasolmuista. Tyypillinen benchmark-ohjelma sisältää paljon laskentaa tarvitsevan matemaattisen algoritmin, jota käytetään tieteellisissä ohjelmistoissa. Benchmarkista riippuen tulosten ymmärtäminen ja hyödyntäminen voi olla haasteellista.

Soft Computing Methods in Metallurgy

In metallurgic plants a high quality metal production is always required. Nowadays soft computing applications are more often used for automation of manufacturing process and quality control instead of mechanical techniques. In this thesis an overview of soft computing methods presents. As an example of soft computing application, an effective model of fuzzy expert system for the automotive quality control of steel degassing process was developed. The purpose of this work is to describe the fuzzy relations as quality hypersurfaces by varying number of linguistic variables and fuzzy sets.

Evolutionary computing in search-based software engineering

This master’s thesis aims to study and represent from literature how evolutionary algorithms are used to solve different search and optimisation problems in the area of software engineering. Evolutionary algorithms are methods, which imitate the natural evolution process. An artificial evolution process evaluates fitness of each individual, which are solution candidates. The next population of candidate solutions is formed by using the good properties of the current population by applying different mutation and crossover operations. Different kinds of evolutionary algorithm applications related to software engineering were searched in the literature. Applications were classified and represented. Also the necessary basics about evolutionary algorithms were presented. It was concluded, that majority of evolutionary algorithm applications related to software engineering were about software design or testing. For example, there were applications about classifying software production data, project scheduling, static task scheduling related to parallel computing, allocating modules to subsystems, N-version programming, test data generation and generating an integration test order. Many applications were experimental testing rather than ready for real production use. There were also some Computer Aided Software Engineering tools based on evolutionary algorithms.

Use of scenario analysis in studying emerging technology – Case Grid computing

Tutkimuksen selvitettiin miten skenaarioanalyysia voidaan käyttää uuden teknologian tutkimisessa. Työssä havaittiin, että skenaarioanalyysin soveltuvuuteen vaikuttaa eniten teknologisen muutoksen taso ja saatavilla olevan tiedon luonne. Skenaariomenetelmä soveltuu hyvin uusien teknologioiden tutkimukseen erityisesti radikaalien innovaatioiden kohdalla. Syynä tähän on niihin liittyvä suuri epävarmuus, kompleksisuus ja vallitsevan paradigman muuttuminen, joiden takia useat muut tulevaisuuden tutkimuksen menetelmät eivät ole tilanteessa käyttökelpoisia. Työn empiirisessä osiossa tutkittiin hilaverkkoteknologian tulevaisuutta skenaarioanalyysin avulla. Hilaverkot nähtiin mahdollisena disruptiivisena teknologiana, joka radikaalina innovaationa saattaa muuttaa tietokonelaskennan nykyisestä tuotepohjaisesta laskentakapasiteetin ostamisesta palvelupohjaiseksi. Tällä olisi suuri vaikutus koko nykyiseen ICT-toimialaan erityisesti tarvelaskennan hyödyntämisen ansiosta. Tutkimus tarkasteli kehitystä vuoteen 2010 asti. Teorian ja olemassa olevan tiedon perusteella muodostettiin vahvaan asiantuntijatietouteen nojautuen neljä mahdollista ympäristöskenaariota hilaverkoille. Skenaarioista huomattiin, että teknologian kaupallinen menestys on vielä monen haasteen takana. Erityisesti luottamus ja lisäarvon synnyttäminen nousivat tärkeimmiksi hilaverkkojen tulevaisuutta ohjaaviksi tekijöiksi.

Computing the diameter of Coxeter groups

This thesis addresses the problem of computing the minimal and maximal diameter of the Cayley graph of Coxeter groups. We first present and assert relevant parts of polytope theory and related Coxeter theory. After this, a method of contracting the orthogonal projections of a polytope from Rd onto R2 and R3, d ¸ 3 is presented. This method is the Equality Set Projection algorithm that requires a constant number of linearprogramming problems per facet of the projection in the absence of degeneracy. The ESP algorithm allows us to compute also projected geometric diameters of high-dimensional polytopes. A representation set of projected polytopes is presented to illustrate the methods adopted in this thesis.

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.

Memristive Computing

Memristive computing refers to the utilization of the memristor, the fourth fundamental passive circuit element, in computational tasks. The existence of the memristor was theoretically predicted in 1971 by Leon O. Chua, but experimentally validated only in 2008 by HP Labs. A memristor is essentially a nonvolatile nanoscale programmable resistor — indeed, memory resistor — whose resistance, or memristance to be precise, is changed by applying a voltage across, or current through, the device. Memristive computing is a new area of research, and many of its fundamental questions still remain open. For example, it is yet unclear which applications would benefit the most from the inherent nonlinear dynamics of memristors. In any case, these dynamics should be exploited to allow memristors to perform computation in a natural way instead of attempting to emulate existing technologies such as CMOS logic. Examples of such methods of computation presented in this thesis are memristive stateful logic operations, memristive multiplication based on the translinear principle, and the exploitation of nonlinear dynamics to construct chaotic memristive circuits. This thesis considers memristive computing at various levels of abstraction. The first part of the thesis analyses the physical properties and the current-voltage behaviour of a single device. The middle part presents memristor programming methods, and describes microcircuits for logic and analog operations. The final chapters discuss memristive computing in largescale applications. In particular, cellular neural networks, and associative memory architectures are proposed as applications that significantly benefit from memristive implementation. The work presents several new results on memristor modeling and programming, memristive logic, analog arithmetic operations on memristors, and applications of memristors. The main conclusion of this thesis is that memristive computing will be advantageous in large-scale, highly parallel mixed-mode processing architectures. This can be justified by the following two arguments. First, since processing can be performed directly within memristive memory architectures, the required circuitry, processing time, and possibly also power consumption can be reduced compared to a conventional CMOS implementation. Second, intrachip communication can be naturally implemented by a memristive crossbar structure.

Near-Threshold Computing

Valmistustekniikoiden kehittyessä IC-piireille saadaan mahtumaan yhä enemmän transistoreja. Monimutkaisemmat piirit mahdollistavat suurempien laskutoimitusmäärien suorittamisen aikayksikössä. Piirien aktiivisuuden lisääntyessä myös niiden energiankulutus lisääntyy, ja tämä puolestaan lisää piirin lämmöntuotantoa. Liiallinen lämpö rajoittaa piirien toimintaa. Tämän takia tarvitaan tekniikoita, joilla piirien energiankulutusta saadaan pienennettyä. Uudeksi tutkimuskohteeksi ovat tulleet pienet laitteet, jotka seuraavat esimerkiksi ihmiskehon toimintaa, rakennuksia tai siltoja. Tällaisten laitteiden on oltava energiankulutukseltaan pieniä, jotta ne voivat toimia pitkiä aikoja ilman akkujen lataamista. Near-Threshold Computing on tekniikka, jolla pyritään pienentämään integroitujen piirien energiankulutusta. Periaatteena on käyttää piireillä pienempää käyttöjännitettä kuin piirivalmistaja on niille alunperin suunnitellut. Tämä hidastaa ja haittaa piirin toimintaa. Jos kuitenkin laitteen toiminnassa pystyään hyväksymään huonompi laskentateho ja pienentynyt toimintavarmuus, voidaan saavuttaa säästöä energiankulutuksessa. Tässä diplomityössä tarkastellaan Near-Threshold Computing -tekniikkaa eri näkökulmista: aluksi perustuen kirjallisuudesta löytyviin aikaisempiin tutkimuksiin, ja myöhemmin tutkimalla Near-Threshold Computing -tekniikan soveltamista kahden tapaustutkimuksen kautta. Tapaustutkimuksissa tarkastellaan FO4-invertteriä sekä 6T SRAM -solua piirisimulaatioiden avulla. Näiden komponenttien käyttäytymisen Near-Threshold Computing –jännitteillä voidaan tulkita antavan kattavan kuvan suuresta osasta tavanomaisen IC-piirin pinta-alaa ja energiankulusta. Tapaustutkimuksissa käytetään 130 nm teknologiaa, ja niissä mallinnetaan todellisia piirivalmistusprosessin tuotteita ajamalla useita Monte Carlo -simulaatioita. Tämä valmistuskustannuksiltaan huokea teknologia yhdistettynä Near-Threshold Computing -tekniikkaan mahdollistaa matalan energiankulutuksen piirien valmistaminen järkevään hintaan. Tämän diplomityön tulokset näyttävät, että Near-Threshold Computing pienentää piirien energiankulutusta merkittävästi. Toisaalta, piirien nopeus heikkenee, ja yleisesti käytetty 6T SRAM -muistisolu muuttuu epäluotettavaksi. Pidemmät polut logiikkapiireissä sekä transistorien kasvattaminen muistisoluissa osoitetaan tehokkaiksi vastatoimiksi Near- Threshold Computing -tekniikan huonoja puolia vastaan. Tulokset antavat perusteita matalan energiankulutuksen IC-piirien suunnittelussa sille, kannattaako käyttää normaalia käyttöjännitettä, vai laskea sitä, jolloin piirin hidastuminen ja epävarmempi käyttäytyminen pitää ottaa huomioon.

On Energy Efficient Computing Platforms

In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.

What are the opportunities and challenges of cloud computing technology in the healthcare information systems

This thesis discusses the opportunities and challenges of the cloud computing technology in healthcare information systems by reviewing the existing literature on cloud computing and healthcare information system and the impact of cloud computing technology to healthcare industry. The review shows that if problems related to security of data are solved then cloud computing will positively transform the healthcare institutions by giving advantage to the healthcare IT infrastructure as well as improving and giving benefit to healthcare services. Therefore, this thesis will explore the opportunities and challenges that are associated with cloud computing in the context of Finland in order to help the healthcare organizations and stakeholders to determine its direction when it decides to adopt cloud technology on their information systems.

Video transcoding in a distributed cloud computing environment

Video transcoding refers to the process of converting a digital video from one format into another format. It is a compute-intensive operation. Therefore, transcoding of a large number of simultaneous video streams requires a large amount of computing resources. Moreover, to handle di erent load conditions in a cost-e cient manner, the video transcoding service should be dynamically scalable. Infrastructure as a Service Clouds currently offer computing resources, such as virtual machines, under the pay-per-use business model. Thus the IaaS Clouds can be leveraged to provide a coste cient, dynamically scalable video transcoding service. To use computing resources e ciently in a cloud computing environment, cost-e cient virtual machine provisioning is required to avoid overutilization and under-utilization of virtual machines. This thesis presents proactive virtual machine resource allocation and de-allocation algorithms for video transcoding in cloud computing. Since users' requests for videos may change at di erent times, a check is required to see if the current computing resources are adequate for the video requests. Therefore, the work on admission control is also provided. In addition to admission control, temporal resolution reduction is used to avoid jitters in a video. Furthermore, in a cloud computing environment such as Amazon EC2, the computing resources are more expensive as compared with the storage resources. Therefore, to avoid repetition of transcoding operations, a transcoded video needs to be stored for a certain time. To store all videos for the same amount of time is also not cost-e cient because popular transcoded videos have high access rate while unpopular transcoded videos are rarely accessed. This thesis provides a cost-e cient computation and storage trade-o strategy, which stores videos in the video repository as long as it is cost-e cient to store them. This thesis also proposes video segmentation strategies for bit rate reduction and spatial resolution reduction video transcoding. The evaluation of proposed strategies is performed using a message passing interface based video transcoder, which uses a coarse-grain parallel processing approach where video is segmented at group of pictures level.

Development of agnostic mobile applications with cross-platform cloud computing platforms

Smart phones became part and parcel of our life, where mobility provides a freedom of not being bounded by time and space. In addition, number of smartphones produced each year is skyrocketing. However, this also created discrepancies or fragmentation among devices and OSes, which in turn made an exceeding hard for developers to deliver hundreds of similar featured applications with various versions for the market consumption. This thesis is an attempt to investigate whether cloud based mobile development platforms can mitigate and eventually eliminate fragmentation challenges. During this research, we have selected and analyzed the most popular cloud based development platforms and tested integrated cloud features. This research showed that cloud based mobile development platforms may able to reduce mobile fragmentation and enable to utilize single codebase to deliver a mobile application for different platforms.

Analyzing and Computing the Sustainability Gains of Building Automation

Smart home implementation in residential buildings promises to optimize energy usage and save significant amount of energy simply due to a better understanding of user's energy usage profile. Apart from the energy optimisation prospects of this technology, it also aims to guarantee occupants significant amount of comfort and remote control over home appliances both at home locations and at remote places. However, smart home investment just like any other kind of investment requires an adequate measurement and justification of the economic gains it could proffer before its realization. These economic gains could differ for different occupants due to their inherent behaviours and tendencies. Thus it is pertinent to investigate the various behaviours and tendencies of occupants in different domain of interests and to measure the value of the energy savings accrued by smart home implementations in these domains of interest in order to justify such economic gains. This thesis investigates two domains of interests (the rented apartment and owned apartment) for primarily two behavioural tendencies (Finland and Germany) obtained from observation and corroborated by conducted interviews to measure the payback time and Return on Investment (ROI) of their smart home implementations. Also, similar measures are obtained for identified Australian use case. The research finding reveals that building automation for the Finnish behavioural tendencies seems to proffers a better ROI and payback time for smart home implementations.

Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.