scholarly journals Analytical and Numerical Evaluation of Co-Scheduling Strategies and Their Application

2021 ◽  
Author(s):  
Ruslan Kuchumov ◽  
Vladimir Korkhov
Keyword(s):  
Optimal Strategy ◽  
High Performance ◽  
A Priori ◽  
Scheduling Problem ◽  
Heuristic Strategies ◽  
Accuracy Of Measurement ◽  
Online Strategy ◽  
Scheduling Strategies ◽  
Priori Information ◽  
Computational Resources

Applications in high-performance computing (HPC) may not use all available computational resources, leaving some of them underutilized. By co-scheduling, i.e. running more than one application on the same computational node, it is possible to improve resource utilization and overall throughput. Some applications may have conflicting requirements on resources and co-scheduling may cause performance degradation, so it is important to take it into account in scheduling decisions. In this paper, we formalized co-scheduling problem and proposed multiple scheduling strategies to solve it: an optimal strategy, an online strategy and heuristic strategies. These strategies vary in terms of the optimality of the solution they produce and a priori information about the system they require. We showed theoretically that the online strategy provides schedules with a competitive ratio that has a constant upper limit. This allowed us to solve the co-scheduling problem using heuristic strategies that approximate this online strategy. Numerical simulations showed how heuristic strategies compare to the optimal strategy for different input systems. We proposed a method for measuring input parameters of the model in practice and evaluated this method on HPC benchmark applications. We showed high accuracy of measurement method, which allows to apply proposed scheduling strategies in scheduler implementation.

scholarly journals Analytical and Numerical Evaluation of Co-Scheduling Strategies and Their Application

Computers ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 122
Author(s):  
Ruslan Kuchumov ◽  
Vladimir Korkhov
Keyword(s):  
Optimal Strategy ◽  
High Performance ◽  
A Priori ◽  
Scheduling Problem ◽  
Heuristic Strategies ◽  
Online Strategy ◽  
Scheduling Strategies ◽  
Priori Information ◽  
Computational Resources ◽  
Performance Computing

Applications in high-performance computing (HPC) may not use all available computational resources, leaving some of them underutilized. By co-scheduling, i.e., running more than one application on the same computational node, it is possible to improve resource utilization and overall throughput. Some applications may have conflicting requirements on resources and co-scheduling may cause performance degradation, so it is important to take it into account in scheduling decisions. In this paper, we formalize the co-scheduling problem and propose multiple scheduling strategies to solve it: an optimal strategy, an online strategy and heuristic strategies. These strategies vary in terms of the optimality of the solution they produce and a priori information about the system they require. We show theoretically that the online strategy provides schedules with a competitive ratio that has a constant upper limit. This allows us to solve the co-scheduling problem using heuristic strategies that approximate this online strategy. Numerical simulations show how heuristic strategies compare to the optimal strategy for different input systems. We propose a method for measuring input parameters of the model in practice and evaluate this method on HPC benchmark applications. We show the high accuracy of the measurement method, which allows us to apply the proposed scheduling strategies in the scheduler implementation.

An Offline-Online Strategy for Goal-Oriented Coverage Path Planning using A Priori Information

2021 ◽  
Author(s):  
Zeba Khanam ◽  
Sangeet Saha ◽  
Dimitri Ognibene ◽  
Klaus McDonald-Maier ◽  
Shoaib Ehsan
Keyword(s):  
Path Planning ◽  
A Priori ◽  
A Priori Information ◽  
Coverage Path Planning ◽  
Online Strategy ◽  
Priori Information

Extraction of Specific Signals with Temporal Structure

2001 ◽  
Vol 13 (9) ◽  
pp. 1995-2003 ◽  
Author(s):  
Allan Kardec Barros ◽  
Andrzej Cichocki
Keyword(s):  
High Performance ◽  
Learning Algorithm ◽  
Temporal Structure ◽  
A Priori ◽  
Real Data ◽  
Primary Sources ◽  
Source Signal ◽  
Priori Information ◽  
Blind Extraction ◽  
Linear Mixtures

In this work we develop a very simple batch learning algorithm for semi-blind extraction of a desired source signal with temporal structure from linear mixtures. Although we use the concept of sequential blind extraction of sources and independent component analysis, we do not carry out the extraction in a completely blind manner; neither do we assume that sources are statistically independent. In fact, we show that the a priori information about the autocorrelation function of primary sources can be used to extract the desired signals (sources of interest) from their linear mixtures. Extensive computer simulations and real data application experiments confirm the validity and high performance of the proposed algorithm.

A Model of High Performance Dynamometer

1994 ◽  
Vol 116 (3) ◽  
pp. 279-288 ◽  
Author(s):  
Y. L. Chung ◽  
S. A. Spiewak
Keyword(s):  
High Performance ◽  
Manufacturing Systems ◽  
Dynamic Properties ◽  
A Priori ◽  
Difficult Problem ◽  
Signal Frequency ◽  
Successful Implementation ◽  
Operating Environments ◽  
Self Tuning ◽  
Priori Information

A narrow frequency bandwidth, strong fluctuations of the gain versus signal frequency and sensitivity to disturbances caused by the operating environments are the most common factors limiting the applicability of sensors in manufacturing systems. Self-tuning filters represent an efficient means of alleviating these limitations. Since the dynamic properties of sensors vary rapidly, a successful implementation of sensors coupled with self-tuning filters hinges upon accurate, real-time adjustments of these filters. The selection of optimum filter settings, based upon the available distorted output signals from the in-process sensors, poses a difficult problem. In general, the algorithm of self tuning requires a priori information about the sensor and its environment, condensed into a form of an analytical model. A systematic approach to the analytical modeling of sensors is proposed. To illustrate this approach, a comprehensive model of a commercial dynamometer is developed and tested.

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

scholarly journals Computational Method for Wavefront Sensing Based on Transport-Of-Intensity Equation

Photonics ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 177
Author(s):  
Iliya Gritsenko ◽  
Michael Kovalev ◽  
George Krasin ◽  
Matvey Konoplyov ◽  
Nikita Stsepuro
Keyword(s):  
A Priori ◽  
Spherical Wave ◽  
Computational Method ◽  
Optical Systems ◽  
Radius Of Curvature ◽  
Imaging Method ◽  
Wavefront Sensing ◽  
Phase Imaging ◽  
Transport Of Intensity Equation ◽  
Priori Information

Recently the transport-of-intensity equation as a phase imaging method turned out as an effective microscopy method that does not require the use of high-resolution optical systems and a priori information about the object. In this paper we propose a mathematical model that adapts the transport-of-intensity equation for the purpose of wavefront sensing of the given light wave. The analysis of the influence of the longitudinal displacement z and the step between intensity distributions measurements on the error in determining the wavefront radius of curvature of a spherical wave is carried out. The proposed method is compared with the traditional Shack–Hartmann method and the method based on computer-generated Fourier holograms. Numerical simulation showed that the proposed method allows measurement of the wavefront radius of curvature with radius of 40 mm and with accuracy of ~200 μm.

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