Application and support for high-performance simulation

types: Editorial CommentHigh performance simulation that supports sophisticated simulation experimentation and optimization can require non-trivial amounts of computing power. Advanced distributed computing techniques and systems found in areas such as High Performance Computing (HPC), High Throughput Computing (HTC), grid computing, cloud computing and e-Infrastructures are needed to provide effectively the computing power needed for the high performance simulation of large and complex models. In simulation there has been a long tradition of translating and adopting advances in distributed computing as shown by contributions from the parallel and distributed simulation community. This special issue brings together a contemporary collection of work showcasing original research in the advancement of simulation theory and practice with distributed computing. This special issue is divided into two parts. This first part focuses on research pertaining to high performance simulation that support a range of applications including the study of epidemics, social networks, urban mobility and real-time embedded and cyber-physical systems. Compared to other simulation techniques agent-based modeling and simulation is relatively new; however, it is increasingly being used to study large-scale problems. Agent-based simulations present challenges for high performance simulation as they can be complex and computationally demanding, and it is therefore not surprising that this special issue includes several articles on the high performance simulation of such systems.Research Councils U

Parallel and Distributed Machine Learning Algorithms for Scalable Big Data Analytics

This editorial is for the Special Issue of the journal Future Generation Computing Systems, consisting of the selected papers of the 6th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning 2017). In this editorial, we have given a high-level overview of the 4 papers contained in this special issue, along with references to some of the related works

Expert systems: Special issue on “New trends and Innovations in Intelligent Distributed Computing”

[Excerpt] Distributed Systems current face new challenges of adapting and reusing research results in the area of Intelligent Systems. Intelligent Systems use methods and technology derived from Knowledge‐based and Computational Intelligence. Distributed Computing develops methods and technology to build systems composed of collaborating components. The fast growth of both Big Data and Data Mining have created interesting challenges for classical methods, algorithms, and frameworks from Distributed Computing, which makes especially interesting analysis and research into new trends and innovations that have recently appeared in this area. This special issue welcomed submissions of original papers introducing research results on all the aspects covering the roles of Knowledge and Intelligence in Distributed Systems, ranging from concepts and theoretical developments to advanced technologies and innovative applications. This issue presents a expanded versions of these papers from the best of those presented at the 10th International Symposium on Intelligent Distributed Computing (IDC 2016), which was held in Paris (France). [...]As the special issue editors, we would like to take this opportunity to thank the various authors for their papers and the reviewers fortheir work. We are also grateful to Jon Hall, Editor-in-Chief of the Wiley journal Expert Systems. We would like to particularly thankthe IDC'16 programme committee members for their hard work and dedication. To conclude, we would like to acknowledge the financialsupport received from Spanish Ministry of Economy and Competitiveness (MINECO) projects: EphemeCH (TIN2014-56494-C4-{1… 4}-P)and DeepBio (TIN2017-85727-C4-{1… 4}-P), both under the European Regional Development Fund FEDER and the support by COMPETE:POCI-01-0145-FEDER-007043 and FCT Fundao para a Cincia e Tecnologia within the Project Scope: UID/CEC/00319/2013

Investigation of cluster and cluster queuing system

Cluster became main platform as parallel and distributed computing structure for high performance computing. Following the development of high performance computer architecture more and more different branches of natural science benefit fromhuge and efficient computational power. For instance bio-informatics, climate science, computational physics, computational chemistry, marine science, etc. Efficient and reliable computing powermay not only expending demand of existing high performance computing users but also attracting more and more different users. Efficiency and performance are main factors on high performance computing. Most of the high performance computer exists as computer cluster. Computer clustering is the popular and main stream of high-performance computing. Discover the efficiency of high performance computing or cluster is very interesting and never enough as it is really depending on different users. Monitoring and tuning high performance or cluster facilities are always necessary. This project focuses on high performance computer monitoring. Comparing queuing status and work load on different computing nodes on the cluster. As the power consumption is main issue nowadays, our project will also try to estimate power consumption on these special sites and also try to support our way of doing estimation.Master i nettverks- og systemadministrasjo