Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Valgrind is a dynamic binary translation and instrumentation framework. It is suited to analysing memory usage. It is used in memory validation and profiling tools. Currently, Valgrind is restricted to executing a guest with serialised thread scheduling. This results in lost opportunity for performance when analysing highly parallel applications on parallel architectures. We have extended the framework...
We show that the problem of finding an energy minimal schedule for execution of a collection of jobs on a multiprocessor with job migration allowed has polynomial complexity. Each job is specified by a release time, a deadline, and an amount of work to be performed. All of the processors have the same, convex power-speed trade-off of the form P = phi(s), where P is power, s is speed, and phi is convex...
In HPC, power-related concern becomes dominant aspects of hardware and software design. Significant research effort has been devoted towards the energy optimization of parallel loop. This article is focused on energy-oriented OpenMP static and dynamic parallel loop scheduling problem. Only DVS cannot obtain the maximum energy savings. It is necessary to combine parallel loop rescheduling and DVS....
In this work, we study the behaviour of different resource scheduling strategies when doing job orchestration in grid environments. We empirically demonstrate that scheduling strategies based on reinforcement learning are a good choice to improve the overall performance of grid applications and resource utilization.
In this paper, we tackle the problem of scheduling tasks of an Ocean-Atmosphere application used for climate prediction over the Grid. We have designed scheduling solutions for both homogeneous and heterogeneous platforms which have been tested in real experiments on Grid'5000. Additionally we compare our simulations with real experiments to see how accurate our simulations are.
TinyOS is the current state of the art in operating systems for sensor network research. Event- based programming model of TinyOS presents concept of Task to allow postponing processing. For little processing and memory overhead and to avoid race conditions, tasks are non-preemptive. This causes executing long running task reduce system responsiveness. In general two approaches suggested for solving...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.