Visualizing classification of natural video sequences using sparse, hierarchical models of cortex.

Recent work on hierarchical models of visual cortex has reported state-of-the-art accuracy on whole-scene labeling using natural still imagery. This raises the question of whether the reported accuracy may be due to the sophisticated, non-biological back-end supervised classifiers typically used (support vector machines) and/or the limited number of images used in these experiments. In particular, is the model classifying features from the object or the background? Previous work (Landecker, Brumby, et al., COSYNE 2010) proposed tracing the spatial support of a classifier’s decision back through a hierarchical cortical model to determine which parts of the image contributed to the classification, compared to the positions of objects in the scene. In this way, we can go beyond standard measures of accuracy to provide tools for visualizing and analyzing high-level object classification. We now describe new work exploring the extension of these ideas to detection of objects in video sequences of natural scenes

Optimizing job performance under a given power constraint in HPC centers

Never-ending striving for performance has resulted in a tremendous increase in power consumption of HPC centers. Power budgeting has become very important from several reasons such as reliability, operating costs and limited power draw due to the existing infrastructure. In this paper we propose a power budget guided job scheduling policy that maximize overall job performance for a given power budget. We have shown that using DVFS under a power constraint performance can be significantly improved as it allows more jobs to run simultaneously leading to shorter wait times. Aggressiveness of frequency scaling applied to a job depends on instantaneous power consumption and on the job's predicted performance. Our policy has been evaluated for four workload traces from systems in production use with up to 4 008 processors. The results show that our policy achieves up to two times better performance compared to power budgeting without DVFS. Moreover it leads to 23% lower CPU energy consumption on average. Furthermore, we have investigated how much job performance and energy efficiency can be improved under our policy and same power budget by an increase in the number of DVFS enabled processors.Peer ReviewedPostprint (published version

Mixing multi-core CPUs and GPUs for scientific simulation software

Recent technological and economic developments have led to widespread availability of multi-core CPUs and specialist accelerator processors such as graphical processing units (GPUs). The accelerated computational performance possible from these devices can be very high for some applications paradigms. Software languages and systems such as NVIDIA's CUDA and Khronos consortium's open compute language (OpenCL) support a number of individual parallel application programming paradigms. To scale up the performance of some complex systems simulations, a hybrid of multi-core CPUs for coarse-grained parallelism and very many core GPUs for data parallelism is necessary. We describe our use of hybrid applica- tions using threading approaches and multi-core CPUs to control independent GPU devices. We present speed-up data and discuss multi-threading software issues for the applications level programmer and o er some suggested areas for language development and integration between coarse-grained and ne-grained multi-thread systems. We discuss results from three common simulation algorithmic areas including: partial di erential equations; graph cluster metric calculations and random number generation. We report on programming experiences and selected performance for these algorithms on: single and multiple GPUs; multi-core CPUs; a CellBE; and using OpenCL. We discuss programmer usability issues and the outlook and trends in multi-core programming for scienti c applications developers

A Sonic Intervention Into Authenticity And Black Metal

This thesis is an intervention into the world of black metal and the role that authenticity plays within the politics of the subgenre. I explore the evolution and escalation that takes place between the theatrics, the music, and violence committed in the clamoring to be perceived as ‘true’ metal. Throughout my thesis I use a variety of approaches to create a holistic view of black metal as a subgenre and analyze the ways in which it evolved. My primary focus was studying the music itself, paired with lyrics and later subcultural analysis of my selected bands. As a fan and a scholar, I assert that authenticity not only plays a huge role in the politics of music subcultures, but for culture as a whole. In the case of this thesis, the politics of authenticity in the second wave of black metal may have resulted in arson, suicide, and murder and, at the very least, the reports of this behavior served as a foundational mythology for the subgenre since the 1990s. Overall, this thesis contributes to the new ways of studying music, subculture, and sound from a rhetorical perspective to trailblaze a path for future scholars in rhetorical, metal music, and sound studies

A Sonic Intervention Into Authenticity And Black Metal

This thesis is an intervention into the world of black metal and the role that authenticity plays within the politics of the subgenre. I explore the evolution and escalation that takes place between the theatrics, the music, and violence committed in the clamoring to be perceived as ‘true’ metal. Throughout my thesis I use a variety of approaches to create a holistic view of black metal as a subgenre and analyze the ways in which it evolved. My primary focus was studying the music itself, paired with lyrics and later subcultural analysis of my selected bands. As a fan and a scholar, I assert that authenticity not only plays a huge role in the politics of music subcultures, but for culture as a whole. In the case of this thesis, the politics of authenticity in the second wave of black metal may have resulted in arson, suicide, and murder and, at the very least, the reports of this behavior served as a foundational mythology for the subgenre since the 1990s. Overall, this thesis contributes to the new ways of studying music, subculture, and sound from a rhetorical perspective to trailblaze a path for future scholars in rhetorical, metal music, and sound studies

DVFS power management in HPC systems

Recent increase in performance of High Performance Computing (HPC) systems has been followed by even higher increase in power consumption. Power draw of modern supercomputers leads to very high operating costs and reliability concerns. Furthermore, it has negative consequences on the environment. Accordingly, over the last decade there have been many works dealing with power/energy management in HPC systems. Since CPUs accounts for a high portion of the total system power consumption, our work aims at CPU power reduction. Dynamic Voltage Frequency Scaling (DVFS) is a widely used technique for CPU power management. Running an application at lower frequency/voltage reduces its power consumption. However, frequency scaling should be used carefully since it has negative effects on the application performance. We argue that the job scheduler level presents a good place for power management in an HPC center having in mind that a parallel job scheduler has a global overview of the entire system. In this thesis we propose power-aware parallel job scheduling policies where the scheduler determines the job CPU frequency, besides the job execution order. Based on the goal, the proposed policies can be classified into two groups: energy saving and power budgeting policies. The energy saving policies aim to reduce CPU energy consumption with a minimal job performance penalty. The first of the energy saving policies assigns the job frequency based on system utilization while the other makes job performance predictions. While for less loaded workloads these policies achieve energy savings, highly loaded workloads suffer from a substantial performance degradation because of higher job wait times due to an increase in load caused by longer job run times. Our results show higher potential of the DVFS technique when applied for power budgeting. The second group of policies are policies for power constrained systems. In contrast to the systems without a power limitation, in the case of a given power budget the DVFS technique even improves overall job performance reducing the average job wait time. This comes from a lower job power consumption that allows more jobs to run simultaneously. The first proposed policy from this group assigns CPU frequency using the job predicted performance and current power draw of already running jobs. The other power budgeting policy is based on an optimization problem which solution determines the job execution order, as well as power distribution among jobs selected for execution. This policy fully exploits available power and leads to further performance improvements. The last contribution of the thesis is an analysis of the DVFS technique potential for energyperformance trade-off in current and future HPC systems. Ongoing changes in technology decrease the DVFS applicability for energy savings but the technique still reduces power consumption making it useful for power constrained systems. In order to analyze DVFS potential, a model of frequency scaling impact on MPI application execution time has been proposed and validated against measurements on a large-scale system. This parametric analysis showed for which application/platform characteristic, frequency scaling leads to energy savings.El aumento de rendimiento que han experimentado los sistemas de altas prestaciones ha venido acompañado de un aumento aún mayor en el consumo de energía. El consumo de los supercomputadores actuales implica unos costes muy altos de funcionamiento. Estos costes no tienen simplemente implicaciones a nivel económico sino también implicaciones en el medio ambiente. Dado la importancia del problema, en los últimos tiempos se han realizado importantes esfuerzos de investigación para atacar el problema de la gestión eficiente de la energía que consumen los sistemas de supercomputación. Dado que la CPU supone un alto porcentaje del consumo total de un sistema, nuestro trabajo se centra en la reducción y gestión eficiente de la energía consumida por la CPU. En concreto, esta tesis se centra en la viabilidad de realizar esta gestión mediante la técnica de Dynamic Voltage Frequency Scalingi (DVFS), una técnica ampliamente utilizada con el objetivo de reducir el consumo energético de la CPU. Sin embargo, esta técnica puede implicar una reducción en el rendimiento de las aplicaciones que se ejecutan, ya que implica una reducción de la frecuencia. Si tenemos en cuenta que el contexto de esta tesis son sistemas de alta prestaciones, minimizar el impacto en la pérdida de rendimiento será uno de nuestros objetivos. Sin embargo, en nuestro contexto, el rendimiento de un trabajo viene determinado por dos factores, tiempo de ejecución y tiempo de espera, por lo que habrá que considerar los dos componentes. Los sistemas de supercomputación suelen estar gestionados por sistemas de colas. Los trabajos, dependiendo de la política que se aplique y el estado del sistema, deberán esperar más o menos tiempo antes de ser ejecutado. Dado las características del sistema objetivo de esta tesis, nosotros consideramos que el Planificador de trabajo (o Job Scheduler), es el mejor componente del sistema para incluir la gestión de la energía ya que es el único punto donde se tiene una visión global de todo el sistema. En este trabajo de tesis proponemos un conjunto de políticas de planificación que considerarán el consumo energético como un recurso más. Estas políticas decidirán que trabajo ejecutar, el número de cpus asignadas y la lista de cpus (y nodos) sino también la frecuencia a la que estas cpus se ejecutarán. Estas políticas estarán orientadas a dos objetivos: reducir la energía total consumida por un conjunto de trabajos y controlar en consumo puntual de un conjunto puntual para evitar saturaciones del sistema en aquellos centros que puedan tener una capacidad limitada (permanente o puntual). El primer grupo de políticas intentará reducir el consumo total minimizando el impacto en el rendimiento. En este grupo encontramos una primera política que asigna la frecuencia de las cpus en función de la utilización del sistema y una segunda que calcula una estimación de la penalización que sufrirá el trabajo que va a empezar para decidir si reducir o no la frecuencia. Estas políticas han mostrado unos resultados aceptables con sistemas poco cargados, pero han mostrado unas pérdidas de rendimiento significativas cuando el sistema está muy cargado. Estas pérdidas de rendimiento no han sido a nivel de incremento significativo del tiempo de ejecución de los trabajos, pero sí de las métricas de rendimiento que incluyen el tiempo de espera de los trabajos (habituales en este contexto). El segundo grupo de políticas, orientadas a sistemas con limitaciones en cuanto a la potencia que pueden consumir, han mostrado un gran potencial utilizando DVFS como mecanismo de gestión. En este caso, comparado con un sistema que no incluya esta gestión, han demostrado mejoras en el rendimiento ya que permiten ejecutar más trabajos de forma simultánea, reduciendo significativamente el tiempo de espera de los trabajos. En este segundo grupo proponemos una política basada en el rendimiento del trabajo que se va a ejecutar y una segunda que considera la asignación de todos los recursos como un problema de optimización lineal. Esta última política es la contribución más importante de la tesis ya que demuestra un buen comportamiento en todos los casos evaluados. La última contribución de la tesis es un estudio del potencial de DVFS como técnica de gestión de la energía en un futuro próximo, en función de un estudio de las características de las aplicaciones, de la reducción de DVFS en el consumo de la CPU y del peso de la CPU dentro de todo el sistema. Este estudio indica que la capacidad de DVFS de ahorrar energía será limitado pero sigue mostrando un gran potencial de cara al control del consumo energético

Resolving the Intergenerational Conflicts of Real Property Law: Preserving Free Markets and Personal Autonomy for Future Generations

This article argues that land allocation agreements (e.g., deeds, mortgages, covenants, easements, etc.) made today will have a profound and perhaps negative effect on owners in future generations. It shows that the current architecture of the land transaction system and related rules unduly favor current owners over successors, causing a negative impact on land markets and choices of future players. Moreover, the article demonstrates that current doctrine and theory do not provide adequate flexibility for future generations to deal with outmoded land allocation agreements, leading to inefficiencies and frustration of the personal autonomy of future owners. The article suggests a new conceptual framework as well as specific alternative approaches for courts and legislatures across the spectrum of real property areas (including, inter alia, interpretation of instruments, the recording system, changed circumstances rules, conservation easements, subdivision covenants, and eminent domain). Given the historical and ongoing importance of land in the American experience, it is essential that decision makers act to guarantee future generations the opportunity to engage in markets and to fulfill their personal aspirations

Resolving the Intergenerational Conflicts of Real Property Law: Preserving Free Markets and Personal Autonomy for Future Generations

This article argues that land allocation agreements (e.g., deeds, mortgages, covenants, easements, etc.) made today will have a profound and perhaps negative effect on owners in future generations. It shows that the current architecture of the land transaction system and related rules unduly favor current owners over successors, causing a negative impact on land markets and choices of future players. Moreover, the article demonstrates that current doctrine and theory do not provide adequate flexibility for future generations to deal with outmoded land allocation agreements, leading to inefficiencies and frustration of the personal autonomy of future owners. The article suggests a new conceptual framework as well as specific alternative approaches for courts and legislatures across the spectrum of real property areas (including, inter alia, interpretation of instruments, the recording system, changed circumstances rules, conservation easements, subdivision covenants, and eminent domain). Given the historical and ongoing importance of land in the American experience, it is essential that decision makers act to guarantee future generations the opportunity to engage in markets and to fulfill their personal aspirations