scholarly journals Automated design and parallelization of programs for heterogeneous platforms using algebra-algorithmic tools

2020 ◽  
pp. 103-114
Author(s):  
А.Yu. Doroshenko ◽  
◽  
O.G. Beketov ◽  
M.M. Bondarenko ◽  
О.А. Yatsenko ◽  
...  
Keyword(s):  
Graphics Processing Units ◽  
Real Life ◽  
Software Tool ◽  
Automatic Parallelization ◽  
Automated Design ◽  
Software Tools ◽  
Heterogeneous Platforms ◽  
Memory Space ◽  
Cyclic Operators ◽  
Rewriting Rules

Methods and software tools for automated design and generation of OpenCL programs based on the algebra of algorithms are proposed. OpenCL is a framework for developing parallel software that executes across heterogeneous platforms consisting of general-purpose processors and/or hardware accelerators. The proposed approach consists in using high-level algebra-algorithmic specifications of programs represented in natural linguistic form and rewriting rules. The developed software tools provide the automated design of algorithm schemes based on a superposition of Glushkov algebra constructs that are considered as reusable components. The tools automatically generate code in a target programming language on the basis of the specifications. In most computing problems, a large part of hardware resources is utilized by computations inside loops, therefore the use of automatic parallelization of cyclic operators is most efficient for them. However, the existing automatic code parallelizing tools, such as Par4All, don’t account the limited amount of accelerator’s onboard memory space while real-life problems demand huge amounts of data to be processed. Thus, there is a need for the development of a parallelization technique embracing the cases of massive computational tasks involving big data. In the paper, a method and a software tool for semi-automatic parallelization of cyclic operators based on loop tiling and data serialization are developed. The parallelization technique uses rewriting rules system to transform programs. The framework for parallelization of loops for optimization of computations using graphics processing units allows semi-automatic parallelization of sequential programs. The approach is illustrated on an example of developing a parallel OpenCL image convolution program.

Effiziente Produktionsgestaltung*/Efficient production design - Development of a software tool for a process- and competence-oriented decision support

2016 ◽  
Vol 106 (07-08) ◽  
pp. 544-549
Author(s):  
V. K. Bellmann ◽  
P. Prof. Nyhuis
Keyword(s):  
Decision Support ◽  
Software Tool ◽  
Software Tools ◽  
Efficient Production ◽  
Design Development ◽  
Huge Amount

Zur Erhaltung ihrer Wettbewerbsfähigkeit setzen Unternehmen sowohl prozessverbessernde als auch kompetenzsteigernde Methoden ein. Jedoch erschwert die Vielzahl an Methoden eine anwendungsspezifische Auswahl. Somit wird ein Software-Tool benötigt, das neben den individuellen Zielstellungen auch die Voraussetzungen für eine erfolgreiche Umsetzung der Methoden berücksichtigt. Dieser Fachbeitrag beschreibt die Entwicklung eines Software-Tools zur zielgerichteten Entscheidungsunterstützung.   Companies apply process-improving and competence-increasing methods to maintain their competitiveness. However the huge amount of existing methods impedes an application-oriented selection. Thus a software tool is needed which considers individual objectives as well as requirements for a successful application of the methods. This paper describes the development of a software tool for a target-oriented decision support.

scholarly journals Beyond Excel: Software Tools and the Accounting Curriculum

2018 ◽  
Vol 13 (1) ◽  
pp. 44-61 ◽  
Author(s):  
Lorraine Lee ◽  
William Kerler ◽  
Daniel Ivancevich
Keyword(s):  
Data Visualization ◽  
Software Tool ◽  
Software Tools ◽  
Adobe Acrobat ◽  
Accounting Information Systems ◽  
Accounting Curriculum ◽  
Experience Levels ◽  
Accounting Practitioners ◽  
Analytic Skills ◽  
Data Analytic

The ability to use various software and tools is important for students entering the accounting profession. In an exploratory study, we develop a survey to assess accounting practitioners' evaluations of the importance of various software tools, as well as the importance of data analytics and data visualization skills. Responses from 197 practitioners indicate that Excel is the most frequently utilized software / tool, the most important software tool for new hires, and that Excel should be emphasized in university accounting programs. We find that the importance of Excel is consistent across different accounting areas (audit, tax, advisory, and corporate) and across all experience levels. In addition, Adobe Acrobat, PowerPoint, accounting / ERP software, and the FASB Codification were identified as frequently utilized across the various accounting areas and experience levels. Finally, practitioners in each of the different accounting areas and at all experience levels indicate data analytic skills and data visualization skills are important, but that data analytic skills are perceived as more important than data visualization skills. Our study contributes to the accounting information systems literature by identifying the specific software and tools that are relevant to the profession and provides guidance on the software and tools that should be emphasized in university accounting programs.

scholarly journals pGlycoQuant with a deep residual network for precise and minuscule-missing-value quantitative glycoproteomics enabling the functional exploration of site-specific glycosylation

2021 ◽  
Author(s):  
Weiqian Cao ◽  
Siyuan Kong ◽  
Wenfeng Zeng ◽  
Pengyun Gong ◽  
Biyun Jiang ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Large Scale ◽  
Missing Values ◽  
Software Tool ◽  
Software Tools ◽  
Residual Network ◽  
Site Specific ◽  
Carcinoma Cell Lines ◽  
L1 Cell Adhesion Molecule

Interpreting large-scale glycoproteomic data for intact glycopeptide identification has been tremendously advanced by software tools. However, software tools for quantitative analysis of intact glycopeptides remain lagging behind, which greatly hinders exploring the differential expression and functions of site-specific glycosylation in organisms. Here, we report pGlycoQuant, a generic software tool for accurate and convenient quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant enables intact glycopeptide quantitation with very low missing values via a deep residual network, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. The pGlycoQuant-based site-specific N-glycoproteomic study conducted here quantifies 6435 intact N-glycopeptides in three hepatocellular carcinoma cell lines with different metastatic potentials and, together with in vitro molecular biology experiments, illustrates core fucosylation at site 979 of the L1 cell adhesion molecule (L1CAM) as a potential regulator of HCC metastasis. pGlycoQuant is freely available at https://github.com/expellir-arma/pGlycoQuant/releases/. We have demonstrated pGlycoQuant to be a powerful tool for the quantitative analysis of site-specific glycosylation and the exploration of potential glycosylation-related biomarker candidates, and we expect further applications in glycoproteomic studies.

scholarly journals Usability Evaluation of Software Tools for Engineering Design

2019 ◽  
Vol 1 (1) ◽  
pp. 1303-1312
Author(s):  
Helena Hashemi Farzaneh ◽  
Lorenz Neuner
Keyword(s):  
Engineering Design ◽  
Design Research ◽  
Evaluation Method ◽  
Software Tool ◽  
Software Tools ◽  
Usability Evaluation ◽  
Smart Devices ◽  
Design Software ◽  
Support Engineering

AbstractMuch of the work in design research focusses on the development of methods and tools to support engineering designers. Many of these tools are nowadays implemented in software. Due to the strongly growing use of computers and smart devices in the last two decades, the expectations of users increased dramatically. In particular users expect good usability, for example little effort for learning to apply the software. Therefore, the usability evaluation of design software tools is crucial. A software tool with bad usability will not be used in industrial practice. Recommendations for usability evaluation of software often stem from the field of Human Computer Interaction. The aim of this paper is to tailor these general approaches to the specific needs of engineering design. In addition, we propose a method to analyse the results of the evaluation and to derive suggestions for improving the design software tool. We apply the usability evaluation method on a use case - the KoMBi software tool for bio-inspired design. The case study provides additional insights with regards to problem, causes and improvement categories.

Powertrain Resilient Mounting Design Analysis

2018 ◽  
Author(s):  
Tigran Parikyan ◽  
Nikola Naranca ◽  
Jochen Neher
Keyword(s):  
Rigid Body ◽  
Modal Analysis ◽  
Frequency Domain ◽  
Static Analysis ◽  
Software Tool ◽  
Software Tools ◽  
Forced Response ◽  
Marine Engine ◽  
Linear Elastic ◽  
Non Linear

For efficient modeling of engine (or powertrain) supported by non-linear elastic mounts, a special methodology has been elaborated. Based on it, software tool has been developed to analyze the motion of rigid body and elastic mounts, which comprises of three modules: • Non-linear static analysis; • Modal analysis (undamped and damped); • Forced response (in frequency domain). Application example of a large V12 marine engine illustrates the suggested workflow. The results are verified against other software tools and validated by measurements.

scholarly journals Sparse matrix partitioning for optimizing SpMV on CPU-GPU heterogeneous platforms

2019 ◽  
Vol 34 (1) ◽  
pp. 66-80 ◽  
Author(s):  
Akrem Benatia ◽  
Weixing Ji ◽  
Yizhuo Wang ◽  
Feng Shi
Keyword(s):  
Graphics Processing Units ◽  
Sparse Matrix ◽  
Sparse Matrices ◽  
Heterogeneous Systems ◽  
Input Matrix ◽  
Heterogeneous Platforms ◽  
Mapping Algorithm ◽  
Matrix Vector Multiplication ◽  
Graphics Processing ◽  
Matrix Partitioning

Sparse matrix–vector multiplication (SpMV) kernel dominates the computing cost in numerous applications. Most of the existing studies dedicated to improving this kernel have been targeting just one type of processing units, mainly multicore CPUs or graphics processing units (GPUs), and have not explored the potential of the recent, rapidly emerging, CPU-GPU heterogeneous platforms. To take full advantage of these heterogeneous systems, the input sparse matrix has to be partitioned on different available processing units. The partitioning problem is more challenging with the existence of many sparse formats whose performances depend both on the sparsity of the input matrix and the used hardware. Thus, the best performance does not only depend on how to partition the input sparse matrix but also on which sparse format to use for each partition. To address this challenge, we propose in this article a new CPU-GPU heterogeneous method for computing the SpMV kernel that combines between different sparse formats to achieve better performance and better utilization of CPU-GPU heterogeneous platforms. The proposed solution horizontally partitions the input matrix into multiple block-rows and predicts their best sparse formats using machine learning-based performance models. A mapping algorithm is then used to assign the block-rows to the CPU and GPU(s) available in the system. Our experimental results using real-world large unstructured sparse matrices on two different machines show a noticeable performance improvement.

Reliability analysis of underground mining equipment using genetic algorithms

2014 ◽  
Vol 20 (1) ◽  
pp. 32-50 ◽  
Author(s):  
Nick Vayenas ◽  
Sihong Peng
Keyword(s):  
Reliability Analysis ◽  
Case Studies ◽  
Reliability Assessment ◽  
Real Life ◽  
Software Tool ◽  
Mining Equipment ◽  
Data Set ◽  
Content Type ◽  
Reliability Centered Maintenance ◽  
Potential Applications

Purpose – While increased mechanization and automation make considerable contributions to mine productivity, unexpected equipment failures and imperfect planned or routine maintenance prohibit the maximum possible utilization of sophisticated mining equipment and require significant amount of extra capital investment. Traditional preventive/planned maintenance is usually scheduled at a fixed interval based on maintenance personnel's experience and it can result in decreasing reliability. This paper deals with reliability analysis and prediction for mining machinery. A software tool called GenRel is discussed with its theoretical background, applied algorithms and its current improvements. In GenRel, it is assumed that failures of mining equipment caused by an array of factors (e.g. age of equipment, operating environment) follow the biological evolution theory. GenRel then simulates the failure occurrences during a time period of interest based on Genetic Algorithms (GAs) combined with a number of statistical procedures. The paper also discusses a case study of two mine hoists. The purpose of this paper is to investigate whether or not GenRel can be applied for reliability analysis of mine hoists in real life. Design/methodology/approach – Statistical testing methods are applied to examine the similarity between the predicted data set with the real-life data set in the same time period. The data employed in this case study is compiled from two mine hoists from the Sudbury area in Ontario, Canada. Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation. Findings – The case studies shown in this paper demonstrate successful applications of a GAs-based software, GenRel, to analyze and predict dynamic reliability characteristics of two hoist systems. Two separate case studies in Mine A and Mine B at a time interval of three months both present acceptable prediction results at a given level of confidence, 5 percent. Practical implications – Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation. Originality/value – Compared to conventional mathematical models, GAs offer several key advantages. To the best of the authors’ knowledge, there has not been a wide application of GAs in hoist reliability assessment and prediction. In addition, the authors bring discrete distribution functions to the software tool (GenRel) for the first time and significantly improve computing efficiency. The results of the case studies demonstrate successful application of GenRel in assessing and predicting hoist reliability, and this may lead to better preventative maintenance management in the industry.

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