A Multilevel Introspective Dynamic Optimization System For Holistic Power-Aware Computing

Power consumption is rapidly becoming the dominant limiting factor for further improvements in computer design. Curiously, this applies both at the "high end" of workstations and servers and the "low end" of handheld devices and embedded computers. At the high-end, the challenge lies in dealing with exponentially growing power densities. At the low-end, there is a demand to make mobile devices more powerful and longer lasting, but battery technology is not improving at the same rate that power consumption is rising. Traditional power-management research is fragmented; techniques are being developed at specific levels, without fully exploring their synergy with other levels. Most software techniques target either operating systems or compilers but do not explore the interaction between the two layers. These techniques also have not fully explored the potential of virtual machines for power management. In contrast, we are developing a system that integrates information from multiple levels of software and hardware, connecting these levels through a communication channel. At the heart of this system are a virtual machine that compiles and dynamically profiles code, and an optimizer that reoptimizes all code, including that of applications and the virtual machine itself. We believe this introspective, holistic approach enables more informed power-management decisions

Achieving High Performance and High Productivity in Next Generational Parallel Programming Languages

Processor design has turned toward parallelism and heterogeneity cores to achieve performance and energy efficiency. Developers find high-level languages attractive because they use abstraction to offer productivity and portability over hardware complexities. To achieve performance, some modern implementations of high-level languages use work-stealing scheduling for load balancing of dynamically created tasks. Work-stealing is a promising approach for effectively exploiting software parallelism on parallel hardware. A programmer who uses work-stealing explicitly identifies potential parallelism and the runtime then schedules work, keeping otherwise idle hardware busy while relieving overloaded hardware of its burden. However, work-stealing comes with substantial overheads. These overheads arise as a necessary side effect of the implementation and hamper parallel performance. In addition to runtime-imposed overheads, there is a substantial cognitive load associated with ensuring that parallel code is data-race free. This dissertation explores the overheads associated with achieving high performance parallelism in modern high-level languages. My thesis is that, by exploiting existing underlying mechanisms of managed runtimes; and by extending existing language design, high-level languages will be able to deliver productivity and parallel performance at the levels necessary for widespread uptake. The key contributions of my thesis are: 1) a detailed analysis of the key sources of overhead associated with a work-stealing runtime, namely sequential and dynamic overheads; 2) novel techniques to reduce these overheads that use rich features of managed runtimes such as the yieldpoint mechanism, on-stack replacement, dynamic code-patching, exception handling support, and return barriers; 3) comprehensive analysis of the resulting benefits, which demonstrate that work-stealing overheads can be significantly reduced, leading to substantial performance improvements; and 4) a small set of language extensions that achieve both high performance and high productivity with minimal programmer effort. A managed runtime forms the backbone of any modern implementation of a high-level language. Managed runtimes enjoy the benefits of a long history of research and their implementations are highly optimized. My thesis demonstrates that converging these highly optimized features together with the expressiveness of high-level languages, gives further hope for achieving high performance and high productivity on modern parallel hardwar

Sistema de recomendação Web usando agentes

O crescimento da Web trouxe vários problemas aos utilizadores. A grande quantidade de informação existente hoje em dia em alguns sítios Web torna a procura de informação útil muito difícil. Os objetivos dos proprietários dos sítios Web e dos utilizadores nem sempre coincidem. O conhecimento dos padrões de visitas dos utilizadores é crucial para que os proprietários possam transformar e adaptar o sítio Web. Este é o princípio do sítio Web adaptativo: o sítio Web adapta-se de forma a melhorar a experiência do utilizador. Alguns algoritmos foram propostos para adaptar um sítio da Web. Neste artigo, descrevemos uma proposta de um sistema de recomendação Web baseado em agentes que combina dois algoritmos: regras de associação e filtragem colaborativa. Ambos os algoritmos são incrementais e funcionam com dados binários. Os resultados mostram que, em algumas situações, a abordagem multiagente melhora a capacidade preditiva quando comparada com os agentes individuais.The growth of the Web has brought several problems for users. Today the vast amount of information on some web sites makes useful information finding very difficult. The objectives of the owners of the web sites and users do not always coincide. The knowledge of patterns of user visits is crucial to the owners to transform and adapt their web site. This is the adaptive website principle: the website adapts to improve the user experience. Some algorithms have been proposed to tailor a website. In this paper, we describe a proposal for a web recommendation system based on agents that combines two algorithms: association rules and collaborative filtering. Both algorithms are incremental and work with binary data. The results show that, in some situations, the multi-agent approach overcomes the predictive capacity of individual agents

The distributed ASCI supercomputer project

The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project

LA TECHNOLOGIE AGENT ET LES RESEAUX SANS FIL

La technologie agent aura un rôle de plus en plus important à jouer dans les télécommunications grâce à leur propriétés, notamment, d'autonomie, d'intelligence et/ou de mobilité. Les réseaux sans fil joueront également un rôle de plus en plus important offrant un accès omniprésent au réseau, favorisant ainsi la mobilité de l'utilisateur. Dans ce contexte, nous avons identifié un certain nombre de domaines d'application des agents dans les réseaux sans fil. Nous avons décrit, ensuite, un exemple d'utilisation des agents en prenant comme scénario de référence un utilisateur de la 4ème génération de mobile ayant à sa disposition plusieurs technologies d'accès sans fil. Cet utilisateur voudra être connecté au mieux, n'importe où, n'importe quand et avec n'importe quel réseau d'accès. La technologie agent est, dans ce cas, utilisée pour adapter le handover horizontal (changement au sein d'une même technologie d'accès) et vertical (changement de technologie d'accès) aux besoins de qualité de service de l'utilisateur