136,331 research outputs found
A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization
Large-scale optimization problems that involve thousands of decision
variables have extensively arisen from various industrial areas. As a powerful
optimization tool for many real-world applications, evolutionary algorithms
(EAs) fail to solve the emerging large-scale problems both effectively and
efficiently. In this paper, we propose a novel Divide-and-Conquer (DC) based EA
that can not only produce high-quality solution by solving sub-problems
separately, but also highly utilizes the power of parallel computing by solving
the sub-problems simultaneously. Existing DC-based EAs that were deemed to
enjoy the same advantages of the proposed algorithm, are shown to be
practically incompatible with the parallel computing scheme, unless some
trade-offs are made by compromising the solution quality.Comment: 12 pages, 0 figure
Automating Fault Tolerance in High-Performance Computational Biological Jobs Using Multi-Agent Approaches
Background: Large-scale biological jobs on high-performance computing systems
require manual intervention if one or more computing cores on which they
execute fail. This places not only a cost on the maintenance of the job, but
also a cost on the time taken for reinstating the job and the risk of losing
data and execution accomplished by the job before it failed. Approaches which
can proactively detect computing core failures and take action to relocate the
computing core's job onto reliable cores can make a significant step towards
automating fault tolerance.
Method: This paper describes an experimental investigation into the use of
multi-agent approaches for fault tolerance. Two approaches are studied, the
first at the job level and the second at the core level. The approaches are
investigated for single core failure scenarios that can occur in the execution
of parallel reduction algorithms on computer clusters. A third approach is
proposed that incorporates multi-agent technology both at the job and core
level. Experiments are pursued in the context of genome searching, a popular
computational biology application.
Result: The key conclusion is that the approaches proposed are feasible for
automating fault tolerance in high-performance computing systems with minimal
human intervention. In a typical experiment in which the fault tolerance is
studied, centralised and decentralised checkpointing approaches on an average
add 90% to the actual time for executing the job. On the other hand, in the
same experiment the multi-agent approaches add only 10% to the overall
execution time.Comment: Computers in Biology and Medicin
A survey on modeling of microgrids - from fundamental physics to phasors and voltage sources
Microgrids have been identified as key components of modern electrical
systems to facilitate the integration of renewable distributed generation
units. Their analysis and controller design requires the development of
advanced (typically model-based) techniques naturally posing an interesting
challenge to the control community. Although there are widely accepted reduced
order models to describe the dynamic behavior of microgrids, they are typically
presented without details about the reduction procedure---hampering the
understanding of the physical phenomena behind them. Preceded by an
introduction to basic notions and definitions in power systems, the present
survey reviews key characteristics and main components of a microgrid. We
introduce the reader to the basic functionality of DC/AC inverters, as well as
to standard operating modes and control schemes of inverter-interfaced power
sources in microgrid applications. Based on this exposition and starting from
fundamental physics, we present detailed dynamical models of the main microgrid
components. Furthermore, we clearly state the underlying assumptions which lead
to the standard reduced model with inverters represented by controllable
voltage sources, as well as static network and load representations, hence,
providing a complete modular model derivation of a three-phase inverter-based
microgrid
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