3,686 research outputs found
Balancing Power Consumption in Multiprocessor Systems
Actions usually taken to prevent processors from overheating, such as decreasing the frequency or stopping the execution flow, also degrade performance. Multiprocessor systems, however, offer the possibility of moving the task that caused a CPU to overheat away to some other, cooler CPU, so throttling becomes only a last resort taken if all of a system\u27s processors are hot. Additionally, the scheduler can take advantage of the energy characteristics of individual tasks, and distribute hot tasks as well as cool tasks evenly among all CPUs.
This work presents a mechanism for determining the energy characteristics of tasks by means of event monitoring counters, and an energy-aware scheduling policy that strives to assign tasks to CPUs in a way that avoids overheating individual CPUs. Our evaluations show that the benefit of avoiding throttling outweighs the overhead of additional task migrations, and that energy-aware scheduling in many cases increases the system\u27s throughput
Radiation safety based on the sky shine effect in reactor
In the reactor operation, neutrons and gamma rays are the most dominant radiation.
As protection, lead and concrete shields are built around the reactor. However, the radiation
can penetrate the water shielding inside the reactor pool. This incident leads to the occurrence
of sky shine where a physical phenomenon of nuclear radiation sources was transmitted
panoramic that extends to the environment. The effect of this phenomenon is caused by the
fallout radiation into the surrounding area which causes the radiation dose to increase. High
doses of exposure cause a person to have stochastic effects or deterministic effects. Therefore,
this study was conducted to measure the radiation dose from sky shine effect that scattered
around the reactor at different distances and different height above the reactor platform. In this
paper, the analysis of the radiation dose of sky shine effect was measured using the
experimental metho
Synthesis of application specific processor architectures for ultra-low energy consumption
In this paper we suggest that further energy savings can be achieved by a new approach to synthesis of embedded processor cores, where the architecture is tailored to the algorithms that the core executes. In the context of embedded processor synthesis, both single-core and many-core, the types of algorithms and demands on the execution efficiency are usually known at the chip design time. This knowledge can be utilised at the design stage to synthesise architectures optimised for energy consumption. Firstly, we present an overview of both traditional energy saving techniques and new developments in architectural approaches to energy-efficient processing. Secondly, we propose a picoMIPS architecture that serves as an architectural template for energy-efficient synthesis. As a case study, we show how the picoMIPS architecture can be tailored to an energy efficient execution of the DCT algorithm
Approximation Algorithms for Energy Minimization in Cloud Service Allocation under Reliability Constraints
We consider allocation problems that arise in the context of service
allocation in Clouds. More specifically, we assume on the one part that each
computing resource is associated to a capacity constraint, that can be chosen
using Dynamic Voltage and Frequency Scaling (DVFS) method, and to a probability
of failure. On the other hand, we assume that the service runs as a set of
independent instances of identical Virtual Machines. Moreover, there exists a
Service Level Agreement (SLA) between the Cloud provider and the client that
can be expressed as follows: the client comes with a minimal number of service
instances which must be alive at the end of the day, and the Cloud provider
offers a list of pairs (price,compensation), this compensation being paid by
the Cloud provider if it fails to keep alive the required number of services.
On the Cloud provider side, each pair corresponds actually to a guaranteed
success probability of fulfilling the constraint on the minimal number of
instances. In this context, given a minimal number of instances and a
probability of success, the question for the Cloud provider is to find the
number of necessary resources, their clock frequency and an allocation of the
instances (possibly using replication) onto machines. This solution should
satisfy all types of constraints during a given time period while minimizing
the energy consumption of used resources. We consider two energy consumption
models based on DVFS techniques, where the clock frequency of physical
resources can be changed. For each allocation problem and each energy model, we
prove deterministic approximation ratios on the consumed energy for algorithms
that provide guaranteed probability failures, as well as an efficient
heuristic, whose energy ratio is not guaranteed
A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems
Recent technological advances have greatly improved the performance and
features of embedded systems. With the number of just mobile devices now
reaching nearly equal to the population of earth, embedded systems have truly
become ubiquitous. These trends, however, have also made the task of managing
their power consumption extremely challenging. In recent years, several
techniques have been proposed to address this issue. In this paper, we survey
the techniques for managing power consumption of embedded systems. We discuss
the need of power management and provide a classification of the techniques on
several important parameters to highlight their similarities and differences.
This paper is intended to help the researchers and application-developers in
gaining insights into the working of power management techniques and designing
even more efficient high-performance embedded systems of tomorrow
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