DocumentCode
3543391
Title
LAMBDA -- The LSDF Execution Framework for Data Intensive Applications
Author
Jejkal, Thomas ; Hartmann, Volker ; Stotzka, Rainer ; Otte, Jens ; García, Ariel ; Van Wezel, Jos ; Streit, Achim
Author_Institution
Inst. for Data Process. & Electron. (IPE), Karlsruhe Inst. of Technol. (KIT), Karlsruhe, Germany
fYear
2012
fDate
15-17 Feb. 2012
Firstpage
213
Lastpage
220
Abstract
To cope with the growing requirements of data intensive scientific experiments, models and simulations the Large Scale Data Facility (LSDF) at KIT aims to support many scientific disciplines. The LSDF is a distributed storage facility at Exabyte scale providing storage, archives, data bases and meta data repositories. Apart from data storage many scientific communities need to perform data processing operations as well. For this purpose the LSDF Execution Framework for Data Intensive Applications (LAMBDA) was developed to allow asynchronous high-performance data processing next to the LSDF. However, it is not restricted to the LSDF or any special feature only available at the LSDF. The main goal of LAMBDA is to simplify large scale data processing for scientific users by reducing complexity, responsibility and error-proneness. The description of an execution is realized as part of LAMBDA administration in the background via meta data that can be obtained from arbitrary sources. Thus, the scientific user has only to select which applications he wants to apply to his data.
Keywords
distributed databases; information retrieval systems; large-scale systems; meta data; storage management; LAMBDA; LSDF execution framework; archives; asynchronous high-performance data processing; complexity reduction; data intensive applications; distributed databases; distributed storage facility; error-proneness reduction; exabyte scale providing storage; large scale data facility; large scale data processing; meta data repositories; responsibility reduction; scientific user; Communities; Data processing; Microscopy; Monitoring; Reliability; Runtime; Software; Hadoop; LSDF; Large Scale Data Facility; data intensive science; data processing; meta data;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel, Distributed and Network-Based Processing (PDP), 2012 20th Euromicro International Conference on
Conference_Location
Garching
ISSN
1066-6192
Print_ISBN
978-1-4673-0226-5
Type
conf
DOI
10.1109/PDP.2012.69
Filename
6169552
Link To Document