The Multi-level Communication: Minimal Deadlock-Free and Storage Efficient Routing for Torus Networks

2014 ◽  
Author(s):  
M.B. Hadim
Keyword(s):  
Multi Level ◽  
Torus Networks ◽  
And Storage

scholarly journals A Multi–Level Approach for Simulation of Storage and Respiration of Produce

2019 ◽  
Vol 9 (6) ◽  
pp. 1052
Author(s):  
Mahmoud Elhalwagy ◽  
Nolan Dyck ◽  
Anthony Straatman
Keyword(s):  
Discrete Element Modelling ◽  
Elementary Volume ◽  
Respiration Model ◽  
Digital Generation ◽  
Flow Heat ◽  
Multi Level ◽  
Simulation Parameters ◽  
And Storage ◽  
Ultimate Purpose ◽  
Generation Procedure

A produce gas respiration model and fruit-stack geometric digital generation approach is used with commercial CFD software (ANSYS CFXTM) to conduct shape-level simulations of the fluid flow, heat and respiration processes that occur during the storage of produce, with the ultimate purpose of providing detailed information that can be used to develop closure coefficients for volume-averaged simulations. A digital generation procedure is used to develop an accurate representation of the shapes of the different produce. The produce shapes are then implemented into a discrete element modelling tool to generate a randomly-distributed stack of produce in a generic container, which is then utilized as a representative elementary volume (REV) for simulations of airflow and respiration. Simulations are first conducted on single pieces of produce and compared to a recently published experimental data for tomatoes and avocadoes to generate coefficients for the respiration model required for the shape-level simulations on the REV. The results of the shape-level simulation are then processed to produce coefficients that can be used for volume-averaged (porous-continuum-level) calculations, which are much more practical for simulations of large areas of storage comprised of hundreds or thousands of boxes of different commodities. The results show that the multi-level approach is a viable means for developing the simulation parameters required to study refrigeration, ripening and storage/transport of produce.

Algorithm Research Based on Distributed Water Multi-Level Resources Scheduling

2014 ◽  
Vol 513-517 ◽  
pp. 2565-2568
Author(s):  
Yi Fan Yuan ◽  
Jiu Li Wang
Keyword(s):  
Genetic Algorithm ◽  
Scheduling Algorithm ◽  
Rapid Development ◽  
Resource Scheduling ◽  
Improved Genetic Algorithm ◽  
Scheduling Policy ◽  
Coding Scheme ◽  
Level Sequence ◽  
Multi Level ◽  
And Storage

With the rapid development of hydropower in China, there are a lot of reservoirs under constructions are put into operation. Therefore, resource scheduling of distributed water conservancy project has become a key focus in current researches. Based on distributed water multi-level resources, the paper put forward to apply the improved genetic algorithm to reservoir resource scheduling. In this way, water level sequence can be the basic genetic algorithm coding scheme, and storage status of reservoir can be stored with the array. Then the genetic algorithm coding can be operated based on the corresponding array index of each reservoir. The paper tries to prove the feasibility of this scheduling policy with some examples, simplifying the process of scheduling algorithm and providing guiding basis for water resource scheduling.

scholarly journals Adaptive method of generation of optimal production orders

2019 ◽  
Vol 110 ◽  
pp. 02127
Author(s):  
Galina Korableva ◽  
Elena Kucherova
Keyword(s):  
Adaptive Method ◽  
Optimization Criterion ◽  
Planning System ◽  
Energy Costs ◽  
Profit Function ◽  
Optimal Production ◽  
Multi Level ◽  
Production Orders ◽  
Product Sales ◽  
And Storage

The article describes the approach to the generation of production or sales orders for enterprises with ordering planning system. The adaptive method of orders’ generation for production and sales of products is multi-level and includes several stages, allowing forming almost optimal package of applications from consumers, obtained by a mathematical model, the optimization criterion of which is the profit function from product sales. The functional structure of the automated decision support system, which is a tool for implementing an adaptive methodology, is considered. The developed method will reduce energy costs during transportation and storage of production orders.

scholarly journals D4.2 Profiling report of the partner’s tools, complete with performance suggestions

2021 ◽  
Author(s):  
R. Amela ◽  
R. Badia ◽  
S. Böhm ◽  
R. Tosi ◽  
C. Soriano ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Programming Model ◽  
Storage Systems ◽  
Performance Suggestions ◽  
Multi Level ◽  
Multiple Levels ◽  
And Performance ◽  
The One ◽  
Dynamic Scheduler ◽  
And Storage

This deliverable focuses on the proling activities developed in the project with the partner's applications. To perform this proling activities, a couple of benchmarks were dened in collaboration with WP5. The rst benchmark is an embarrassingly parallel benchmark that performs a read and then multiple writes of the same object, with the objective of stressing the memory and storage systems and evaluate the overhead when these reads and writes are performed in parallel. A second benchmark is dened based on the Continuation Multi Level Monte Carlo (C-MLMC) algorithm. While this algorithm is normally executed using multiple levels, for the proling and performance analysis objectives, the execution of a single level was enough since the forthcoming levels have similar performance characteristics. Additionally, while the simulation tasks can be executed as parallel (multi-threaded tasks), in the benchmark, single threaded tasks were executed to increase the number of simulations to be scheduled and stress the scheduling engines. A set of experiments based on these two benchmarks have been executed in the MareNostrum 4 supercomputer and using PyCOMPSs as underlying programming model and dynamic scheduler of the tasks involved in the executions. While the rst benchmark was executed several times in a single iteration, the second benchmark was executed in an iterative manner, with cycles of 1) Execution and trace generation; 2) Performance analysis; 3) Improvements. This had enabled to perform several improvements in the benchmark and in the scheduler of PyCOMPSs. The initial iterations focused on the C-MLMC structure itself, performing re-factors of the code to remove ne grain and sequential tasks and merging them in larger granularity tasks. The next iterations focused on improving the PyCOMPSs scheduler, removing existent bottlenecks and increasing its performance by making the scheduler a multithreaded engine. While the results can still be improved, we are satised with the results since the granularity of the simulations run in this evaluation step are much ner than the one that will be used for the real scenarios. The deliverable nishes with some recommendations that should be followed along the project in order to obtain good performance in the execution of the project codes.

An Efficient, Robust, Multi-Level Computational Algorithm for Elastohydrodynamic Lubrication

1989 ◽  
Vol 111 (2) ◽  
pp. 193-199 ◽  
Author(s):  
L. Chang ◽  
T. F. Conry ◽  
C. Cusano
Keyword(s):  
Computational Algorithm ◽  
Point Contact ◽  
Elastohydrodynamic Lubrication ◽  
Contact Problems ◽  
Working Environment ◽  
Ehd Lubrication ◽  
Wide Range ◽  
Direct Iteration ◽  
Multi Level ◽  
And Storage

A new computational algorithm is developed for the numerical analysis of elastohydrodynamic (EHD) lubrication problems. This algorithm combines direct-iteration, Newton-Raphson, and multigrid methods into one working environment. Accurate solutions for a wide range of steady-state, line-contact problems are obtained with a relatively small number of numerical operations. The algorithm can be used to efficiently simulate transient processes in EHD lubrication. It can also be extended to solve point-contact problems with high computational and storage efficiency.

Space-FFT-accelerated marching-on-in-degree methods for finite periodic structures

2009 ◽  
Vol 1 (4) ◽  
pp. 331-337 ◽  
Author(s):  
Amir Geranmayeh ◽  
Wolfgang Ackermann ◽  
Thomas Weiland
Keyword(s):  
Periodic Structures ◽  
Computational Cost ◽  
Stable Solution ◽  
Time Variable ◽  
One Dimensional ◽  
Multi Level ◽  
Temporal And Spatial ◽  
And Storage ◽  
Electric Field Integral Equations ◽  
Field Integral

A fast, yet unconditionally stable, solution of time-domain electric field integral equations (TD EFIE) pertinent to the scattering analysis of uniformly meshed and/or periodic conducting structures is introduced. A one-dimensional discrete fast Fourier transform (FFT)-based algorithm is proffered to expedite the calculation of the recursive spatial convolution products of the Toeplitz–block–Toeplitz retarded interaction matrices in a new marching-without-time-variable scheme. Additional saving owing to the system periodicity is concatenated with the Toeplitz properties due to the uniform discretization in multi-level sense. The total computational cost and storage requirements of the proposed method scale as O(Nt2Nslog Ns) and O(Nt Ns), respectively, as opposed to O(Nt2Ns2) and O(NtNs2) for classical marching-on-in-order methods, where Nt and Ns are the number of temporal and spatial unknowns, respectively. Simulation results for arrays of plate-like and cylindrical scatterers demonstrate the accuracy and efficiency of the technique.

scholarly journals A Narravite Cloud Storage Management using Multi-level Semantic Bonding Technique

2019 ◽  
Vol 8 (2S11) ◽  
pp. 449-453
Keyword(s):  
Cloud Storage ◽  
Clustering Algorithms ◽  
Storage Management ◽  
Storage And Retrieval ◽  
Management Algorithm ◽  
Semantic Classes ◽  
Indexing And Retrieval ◽  
Multi Level ◽  
Semantic Ontology ◽  
And Storage

The problem of cloud storage management has been well studied. The growing size and types of data increases the challenge in storage and retrieval. Number of approaches has been discussed for the problem of storage management. Text based clustering algorithms and Semantic based approaches are defined to improve the performance of storage management. However, the methods suffer to achieve higher performance in indexing and retrieval in terms of storage management. To solve this issue, an efficient semantic bonding measure based clustering and data management algorithm is presented. The method maintains ontology of various classes where each class has been mentioned in multiple levels. Each level of a class has specific properties and values. Using the semantic ontology, the method estimates MSB (Multi-level semantic Bonding) measure for different class of data. The same has been estimated for different level of semantic classes. Indexing of document class is performed based on MSB where the documents similarity has been measured using Topical Closure Measure (TCM). According to the value of TCM, the documents which are similar are identified and merge. The proposed algorithm improves the performance of document clustering and storage management in cloud environment

scholarly journals What are the potential paths for carbon capture and storage in Sweden? A multi-level assessment of historical and current developments

2022 ◽  
Vol 87 ◽  
pp. 102452
Author(s):  
Adrian Lefvert ◽  
Emily Rodriguez ◽  
Mathias Fridahl ◽  
Stefan Grönkvist ◽  
Simon Haikola ◽  
...  
Keyword(s):  
Carbon Capture ◽  
Carbon Capture And Storage ◽  
Multi Level ◽  
And Storage
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