scalable computing
Recently Published Documents


TOTAL DOCUMENTS

115
(FIVE YEARS 19)

H-INDEX

8
(FIVE YEARS 1)

2021 ◽  
Author(s):  
Marek Nowicki ◽  
Łukasz Górski ◽  
Piotr Bała
Keyword(s):  

2021 ◽  
Vol 28 (5) ◽  
pp. 36-42
Author(s):  
Zhi Liu ◽  
Cheng Zhan ◽  
Ying Cui ◽  
Celimuge Wu ◽  
Han Hu

2021 ◽  
Vol 182 (2) ◽  
pp. i-ii
Author(s):  
Dominik Ślęzak ◽  
Tzung-Pei Hong ◽  
Leon S.L. Wang

2021 ◽  
Vol 9 (3) ◽  
pp. 1372-1372
Author(s):  
Hong-Ning Dai Senior ◽  
Zibin Zheng ◽  
Yan Zhang ◽  
Michael Rung Tsong Lyu ◽  
Alberto Nannarelli

2020 ◽  
Vol 20 (6) ◽  
pp. 3-4
Author(s):  
Aneta Karaivanova ◽  
Svetozar Margenov

AbstractWe are pleased to present the special issue “New developments in scalable computing” of the scientific journal “Cybernetics and Information Technologies”. For this issue (Volume 20, No 6 – December 2020), we have selected 19 papers which have gone through peer review and represent novel results in the field of Scalable Computing using state-of-the-art high-performance computing infrastructures.


Author(s):  
Nuwan Goonasekera ◽  
Alexandru Mahmoud ◽  
John Chilton ◽  
Enis Afgan

Abstract Summary The existence of more than 100 public Galaxy servers with service quotas is indicative of the need for an increased availability of compute resources for Galaxy to use. The GalaxyCloudRunner enables a Galaxy server to easily expand its available compute capacity by sending user jobs to cloud resources. User jobs are routed to the acquired resources based on a set of configurable rules and the resources can be dynamically acquired from any of four popular cloud providers (AWS, Azure, GCP or OpenStack) in an automated fashion. Availability and implementation GalaxyCloudRunner is implemented in Python and leverages Docker containers. The source code is MIT licensed and available at https://github.com/cloudve/galaxycloudrunner. The documentation is available at http://gcr.cloudve.org/.


2020 ◽  
Author(s):  
Mario A. R. Dantas

This work presents an introduction to the Data Intensive Scalable Computing (DISC) approach. This paradigm represents a valuable effort to tackle the large amount of data produced by several ordinary applications. Therefore, subjects such as characterization of big data and storage approaches, in addition to brief comparison between HPC and DISC are differentiated highlight.


Sign in / Sign up

Export Citation Format

Share Document