scholarly journals Visualizing systems and software performance - Report on the GI-Dagstuhl seminar for young researchers, July 9-13, 2018

2018 ◽  
Author(s):  
Fabian Beck ◽  
Alexandre Bergel ◽  
Cor-Paul Bezemer ◽  
Katherine E. Isaacs
Keyword(s):  
High Performance ◽  
Community Collaboration ◽  
Software Performance ◽  
Data Systems ◽  
Related Data ◽  
Performance Engineering ◽  
Research Areas ◽  
Performance Report ◽  
Big Data Systems ◽  
Young Researchers

This GI-Dagstuhl seminar addressed the problem of visualizing performance-related data of systems and the software that they run. Due to the scale of performance-related data and the open-ended nature of analyzing it, visualization is often the only feasible way to comprehend, improve, and debug the performance behaviour of systems. The rise of cloud and big data systems, and the rapidly growing scale of the performance-related data that they generate, have led to an increased need for visualization of such data. However, the research communities behind data visualization, performance engineering, and high-performance computing are largely disjunct. The goal of this seminar was to bring together young researchers from these research areas to identify cross-community collaboration and to set the path for long-lasting collaborations towards rich and effective visualizations of performance-related data.

scholarly journals Visualizing systems and software performance - Report on the GI-Dagstuhl seminar for young researchers, July 9-13, 2018

2018 ◽  
Author(s):  
Fabian Beck ◽  
Alexandre Bergel ◽  
Cor-Paul Bezemer ◽  
Katherine E. Isaacs
Keyword(s):  
High Performance ◽  
Community Collaboration ◽  
Software Performance ◽  
Data Systems ◽  
Related Data ◽  
Performance Engineering ◽  
Research Areas ◽  
Performance Report ◽  
Big Data Systems ◽  
Young Researchers

This GI-Dagstuhl seminar addressed the problem of visualizing performance-related data of systems and the software that they run. Due to the scale of performance-related data and the open-ended nature of analyzing it, visualization is often the only feasible way to comprehend, improve, and debug the performance behaviour of systems. The rise of cloud and big data systems, and the rapidly growing scale of the performance-related data that they generate, have led to an increased need for visualization of such data. However, the research communities behind data visualization, performance engineering, and high-performance computing are largely disjunct. The goal of this seminar was to bring together young researchers from these research areas to identify cross-community collaboration and to set the path for long-lasting collaborations towards rich and effective visualizations of performance-related data.

scholarly journals Modeling of distributed file System in big data storage by event- B

2018 ◽  
Vol 210 ◽  
pp. 04042
Author(s):  
Ammar Alhaj Ali ◽  
Pavel Varacha ◽  
Said Krayem ◽  
Roman Jasek ◽  
Petr Zacek ◽  
...  
Keyword(s):  
Big Data ◽  
Data Storage ◽  
High Performance ◽  
File System ◽  
Formal Method ◽  
File Systems ◽  
Distributed File System ◽  
Distributed File Systems ◽  
Data Systems ◽  
Big Data Systems

Nowadays, a wide set of systems and application, especially in high performance computing, depends on distributed environments to process and analyses huge amounts of data. As we know, the amount of data increases enormously, and the goal to provide and develop efficient, scalable and reliable storage solutions has become one of the major issue for scientific computing. The storage solution used by big data systems is Distributed File Systems (DFSs), where DFS is used to build a hierarchical and unified view of multiple file servers and shares on the network. In this paper we will offer Hadoop Distributed File System (HDFS) as DFS in big data systems and we will present an Event-B as formal method that can be used in modeling, where Event-B is a mature formal method which has been widely used in a number of industry projects in a number of domains, such as automotive, transportation, space, business information, medical device and so on, And will propose using the Rodin as modeling tool for Event-B, which integrates modeling and proving as well as the Rodin platform is open source, so it supports a large number of plug-in tools.

scholarly journals LotusSQL: SQL engine for high-performance big data systems

2021 ◽  
Vol 4 (4) ◽  
pp. 252-265
Author(s):  
Xiaohan Li ◽  
Bowen Yu ◽  
Guanyu Feng ◽  
Haojie Wang ◽  
Wenguang Chen
Keyword(s):  
Big Data ◽  
High Performance ◽  
Data Systems ◽  
Big Data Systems

A Study of the Cloud Computing Adoption Issues and Challenges

2020 ◽  
Vol 13 (3) ◽  
pp. 313-318 ◽  
Author(s):  
Dhanapal Angamuthu ◽  
Nithyanandam Pandian
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
Cloud Service ◽  
Ease Of Use ◽  
Modern Trend ◽  
Security Issues ◽  
Research Areas ◽  
Data Location ◽  
Broad Classification

<P>Background: The cloud computing is the modern trend in high-performance computing. Cloud computing becomes very popular due to its characteristic of available anywhere, elasticity, ease of use, cost-effectiveness, etc. Though the cloud grants various benefits, it has associated issues and challenges to prevent the organizations to adopt the cloud. </P><P> Objective: The objective of this paper is to cover the several perspectives of Cloud Computing. This includes a basic definition of cloud, classification of the cloud based on Delivery and Deployment Model. The broad classification of the issues and challenges faced by the organization to adopt the cloud computing model are explored. Examples for the broad classification are Data Related issues in the cloud, Service availability related issues in cloud, etc. The detailed sub-classifications of each of the issues and challenges discussed. The example sub-classification of the Data Related issues in cloud shall be further classified into Data Security issues, Data Integrity issue, Data location issue, Multitenancy issues, etc. This paper also covers the typical problem of vendor lock-in issue. This article analyzed and described the various possible unique insider attacks in the cloud environment. </P><P> Results: The guideline and recommendations for the different issues and challenges are discussed. The most importantly the potential research areas in the cloud domain are explored. </P><P> Conclusion: This paper discussed the details on cloud computing, classifications and the several issues and challenges faced in adopting the cloud. The guideline and recommendations for issues and challenges are covered. The potential research areas in the cloud domain are captured. This helps the researchers, academicians and industries to focus and address the current challenges faced by the customers.</P>

GPU-accelerated molecular dynamics: State-of-art software performance and porting from Nvidia CUDA to AMD HIP

2021 ◽  
pp. 109434202110082
Author(s):  
Nikolay Kondratyuk ◽  
Vsevolod Nikolskiy ◽  
Daniil Pavlov ◽  
Vladimir Stegailov
Keyword(s):  
Molecular Dynamics ◽  
High Performance ◽  
Software Performance ◽  
Computing Systems ◽  
Accelerated Molecular Dynamics ◽  
Nvidia Cuda ◽  
Software And Hardware ◽  
Management Capabilities ◽  
Utilization Time ◽  
Performance Computing

Classical molecular dynamics (MD) calculations represent a significant part of the utilization time of high-performance computing systems. As usual, the efficiency of such calculations is based on an interplay of software and hardware that are nowadays moving to hybrid GPU-based technologies. Several well-developed open-source MD codes focused on GPUs differ both in their data management capabilities and in performance. In this work, we analyze the performance of LAMMPS, GROMACS and OpenMM MD packages with different GPU backends on Nvidia Volta and AMD Vega20 GPUs. We consider the efficiency of solving two identical MD models (generic for material science and biomolecular studies) using different software and hardware combinations. We describe our experience in porting the CUDA backend of LAMMPS to ROCm HIP that shows considerable benefits for AMD GPUs comparatively to the OpenCL backend.

scholarly journals Research on Knowledge Management Models at Universities Using Fuzzy Analytic Hierarchy Process (FAHP)

2021 ◽  
Vol 13 (2) ◽  
pp. 809
Author(s):  
Ngoc Thach Pham ◽  
Anh Duc Do ◽  
Quang Vinh Nguyen ◽  
Van Loi Ta ◽  
Thi Thanh Binh Dao ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Analytic Hierarchy Process ◽  
Fuzzy Analytic Hierarchy Process ◽  
Data Systems ◽  
Knowledge Use ◽  
Analytic Hierarchy ◽  
Priority Order ◽  
Big Data Systems ◽  
Document Review ◽  
Hierarchy Process

This study aims to investigate and evaluate factors related to the knowledge management model at universities in Hanoi, Vietnam. Based on the system literature review (SLR) approach, the study follows descriptive and inductive approach results of the document review process. Eight factors were synthesized with the fuzzy analytic hierarchy process (FAHP) to evaluate the priority order. Ten experts from seven universities participated in the survey. The results rank as follows: (1) knowledge sharing factor (this also has the highest best nonfuzzy performance (BNP) and average multiplier weight (GM)); (2) knowledge management with big data systems; (3) knowledge creation; (4) knowledge use; (5) knowledge gathering; (6) leadership; (7) knowledge rating; and (8) knowledge storage. Discussions, conclusions, limitations of the study, and suggestions for future studies are also mentioned in this study.

Sign in / Sign up

Export Citation Format

Share Document