I denna studie skall Java och C# ställas mot varandra och köras på en Raspberry Pi för att se vilken av dem som kan sortera heltalsvektorer snabbast. Som Java-motor kommer Hot-Spot att användas och Mono för C# och de ska sortera vektorer med sorteringsalgoritmer från språkens stödbibliotek och en implementerad algoritm baserad på urvalssortering. Detta arbete är till för att dem som vill arbeta med ett objektorienterat språk på Raspberry Pi, men inte har bestämt sig än för vilket som skall användas. Resultatet visar att Java presterar bättre än C# i de flesta fall och att det finns undantag då C# presterar bättre. / In this study, Java and C# is set against each other and running on a Raspberry Pi to see if they have similar processing times, or if there is a clear difference between the two languages. As Java-engine HotSpot will be used and Mono for C# and they will sort vectors with sorting algorithms from the language's support library and one implemented algorithm based on selection sort. This work is for those who want to work with an object-oriented language on Raspberry Pi, but has not decided yet on which one to choose. The result shows that Java performs better than C# in most cases, but in some cases C# is performing better.

<p>A few aspects of aircraft noise were evaluated. These were (i) methods of subjective evaluations, (ii) effects of equalization and (iii) the effects of cognitive aspects.</p><p>In the first paper, sorting algorithms were used instead of conventional paired comparison method in order to reduce the number of pairs in the evaluation of subjective judgments. The quick sorting algorithm method revealed more than 99% correlation coefficient with paired comparison method although the method used N*log(N) evaluations instead of N(N-1)/2.</p><p>In the second paper, equalization effects on perception were evaluated in two steps, first with stationary aircraft sounds and second with non-stationary aircraft sounds.</p><p>The first experiment examined the effects of stationary sound segments respect to three different angle positions of the aircrafts relative to the observer (78.7°, 90° & 101.3°), two different SNR conditions (sounds having original broadband plus tonal components versus control broadband sounds having no tonal components) and two different flight conditions (arrival and take-off). Subjects were asked to scale five perceptual attributes (loudness, annoyance, hardness, power and pitch) using Borg CR100 scale. The angle condition showed highly significant effects on annoyance and hardness. Maximal effects were found at an angle of 78.7°. The SNR revealed a significant impact on loudness, power and pitch.</p><p>The second experiment analyzed the effects of tonal components and the problem of appropriate equalization. The spectrum of the signals was modified in two steps (buzz-saw, isolated BPF tone). Further EPNL-equalization, A-, B-, C-, D- and spectral broadband equalizations were applied to the synthesized sounds. Annoyance, loudness, hardness and pitch in the isolated tone conditions showed significantly stronger effects than the buzz-conditions on the perceived judgments. The EPNL-equalization led to a lower degree of differentiation between the spectral conditions compared to B- and C-level equalization.</p><p>In the third paper, the effects of aircraft sounds on children’s cognitive performance were investigated. Impact of aircraft noise on children cognition was found significantly higher in reading comprehensions than in basic mathematics and problem solving tests. It seems children are very sensitive to the modifications in the aircraft noise but further studies are necessary to compliment such a finding.</p>

Les joueurs exigeants acquièrent dès que possible une carte graphique capable de satisfaire leur soif d'immersion dans des jeux dont la précision, le réalisme et l'interactivité redoublent d'intensité au fil du temps. Depuis l'avènement des cartes graphiques dédiées au calcul généraliste, ils n'en sont plus les seuls clients. Dans un premier temps, nous analysons l'apport de ces architectures parallèles spécifiques pour des simulations physiques à grande échelle. Cette étude nous permet de mettre en avant un goulot d'étranglement en particulier limitant la performance des simulations. Partons d'un cas typique : les fissures d'une structure complexe de type barrage en béton armé peuvent être modélisées par un ensemble de particules. La cohésion de la matière ainsi simulée est assurée par les interactions entre elles. Chaque particule est représentée en mémoire par un ensemble de paramètres physiques à consulter systématiquement pour tout calcul de forces entre deux particules. Ainsi, pour que les calculs soient rapides, les données de particules proches dans l'espace doivent être proches en mémoire. Dans le cas contraire, le nombre de défauts de cache augmente et la limite de bande passante de la mémoire peut être atteinte, particulièrement en parallèle, bornant les performances. L'enjeu est de maintenir l'organisation des données en mémoire tout au long de la simulation malgré les mouvements des particules. Les algorithmes de tri standard ne sont pas adaptés car ils trient systématiquement tous les éléments. De plus, ils travaillent sur des structures denses ce qui implique de nombreux déplacements de données en mémoire. Nous proposons PaVo, un algorithme de tri dit adaptatif, c'est-à-dire qu'il sait tirer parti de l'ordre pré-existant dans une séquence. De plus, PaVo maintient des trous dans la structure, répartis de manière à réduire le nombre de déplacements mémoires nécessaires. Nous présentons une généreuse étude expérimentale et comparons les résultats obtenus à plusieurs tris renommés. La diminution des accès à la mémoire a encore plus d'importance pour des simulations à grande échelles sur des architectures parallèles. Nous détaillons une version parallèle de PaVo et évaluons son intérêt. Pour tenir compte de l'irrégularité des applications, la charge de travail est équilibrée dynamiquement par vol de travail. Nous proposons de distribuer automatiquement les données en mémoire de manière à profiter des architectures hiérarchiques. Les tâches sont pré-assignées aux cœurs pour utiliser cette distribution et nous adaptons le moteur de vol pour favoriser des vols de tâches concernant des données proches en mémoire. / Gamers are used to throw onto the latest graphics cards to play immersive games which precision, realism and interactivity keep increasing over time. With general-propose processing on graphics processing units, scientists now participate in graphics card use too. First, we examine these architectures interest for large-scale physics simulations. Drawing on this experience, we highlight in particular a bottleneck in simulations performance. Let us consider a typical situation: cracks in complex reinforced concrete structures such as dams are modelised by many particles. Interactions between particles simulate the matter cohesion. In computer memory, each particle is represented by a set of physical parameters used for every force calculations between two particles. Then, to speed up computations, data from particles close in space should be close in memory. Otherwise, the number of cache misses raises up and memory bandwidth may be reached, specially in parallel environments, limiting global performance. The challenge is to maintain data organization during the simulations despite particle movements. Classical sorting algorithms do not suit such situations because they consistently sort all the elements. Besides, they work upon dense structures leading to a lot of memory transfers. We propose PaVo, an adaptive sort which means it benefits from sequence presortedness. Moreover, to reduce the number of necessary memory transfers, PaVo spreads some gaps inside the data structure. We present a large experimental study and confront results to reputed sort algorithms. Reducing memory requests is again more important for large scale simulations with parallel architectures. We detail a parallel version of PaVo and evaluate its interest. To deal with application irregularities, we do load balancing with work-stealing. We take advantage of hierarchical architectures by automatically distributing data in memory. Thus, tasks are pre-assigned to cores with respect to this organization and we adapt the scheduler to favor steals of tasks working on data close in memory.

A few aspects of aircraft noise were evaluated. These were (i) methods of subjective evaluations, (ii) effects of equalization and (iii) the effects of cognitive aspects. In the first paper, sorting algorithms were used instead of conventional paired comparison method in order to reduce the number of pairs in the evaluation of subjective judgments. The quick sorting algorithm method revealed more than 99% correlation coefficient with paired comparison method although the method used N*log(N) evaluations instead of N(N-1)/2. In the second paper, equalization effects on perception were evaluated in two steps, first with stationary aircraft sounds and second with non-stationary aircraft sounds. The first experiment examined the effects of stationary sound segments respect to three different angle positions of the aircrafts relative to the observer (78.7°, 90° &amp; 101.3°), two different SNR conditions (sounds having original broadband plus tonal components versus control broadband sounds having no tonal components) and two different flight conditions (arrival and take-off). Subjects were asked to scale five perceptual attributes (loudness, annoyance, hardness, power and pitch) using Borg CR100 scale. The angle condition showed highly significant effects on annoyance and hardness. Maximal effects were found at an angle of 78.7°. The SNR revealed a significant impact on loudness, power and pitch. The second experiment analyzed the effects of tonal components and the problem of appropriate equalization. The spectrum of the signals was modified in two steps (buzz-saw, isolated BPF tone). Further EPNL-equalization, A-, B-, C-, D- and spectral broadband equalizations were applied to the synthesized sounds. Annoyance, loudness, hardness and pitch in the isolated tone conditions showed significantly stronger effects than the buzz-conditions on the perceived judgments. The EPNL-equalization led to a lower degree of differentiation between the spectral conditions compared to B- and C-level equalization. In the third paper, the effects of aircraft sounds on children’s cognitive performance were investigated. Impact of aircraft noise on children cognition was found significantly higher in reading comprehensions than in basic mathematics and problem solving tests. It seems children are very sensitive to the modifications in the aircraft noise but further studies are necessary to compliment such a finding.