TY - GEN
T1 - Asterism
T2 - 7th International Workshop on Data-Intensive Computing in the Clouds, DataCloud 2016
AU - Filgueira, Rosa
AU - Silva, Rafael Ferreira Da
AU - Krause, Amrey
AU - Deelman, Ewa
AU - Atkinson, Malcolm
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/2/6
Y1 - 2017/2/6
N2 - We present Asterism, an open source data-intensive framework, which combines the strengths of traditional workflow management systems with new parallel stream-based dataflow systems to run data-intensive applications across multiple heterogeneous resources, without users having to: re-formulate their methods according to different enactment engines; manage the data distribution across systems; parallelize their methods; co-place and schedule their methods with computing resources; and store and transfer large/small volumes of data. We also present the Data-Intensive workflows as a Service (DIaaS) model, which enables easy dataintensive workow composition and deployment on clouds using containers. The feasibility of Asterism and DIaaS model have been evaluated using a real domain application on the NSF-Chameleon cloud. Experimental results shows how Asterism successfully and efficiently exploits combinations of diverse computational platforms, whereas DIaaS delivers specialized software to execute data-intensive applications in a scalable, efficient, and robust way reducing the engineering time and computational cost.
AB - We present Asterism, an open source data-intensive framework, which combines the strengths of traditional workflow management systems with new parallel stream-based dataflow systems to run data-intensive applications across multiple heterogeneous resources, without users having to: re-formulate their methods according to different enactment engines; manage the data distribution across systems; parallelize their methods; co-place and schedule their methods with computing resources; and store and transfer large/small volumes of data. We also present the Data-Intensive workflows as a Service (DIaaS) model, which enables easy dataintensive workow composition and deployment on clouds using containers. The feasibility of Asterism and DIaaS model have been evaluated using a real domain application on the NSF-Chameleon cloud. Experimental results shows how Asterism successfully and efficiently exploits combinations of diverse computational platforms, whereas DIaaS delivers specialized software to execute data-intensive applications in a scalable, efficient, and robust way reducing the engineering time and computational cost.
KW - Data-Intensive science
KW - Deployment and reusability of execution environments
KW - scientific workows
KW - stream-based system
UR - https://www.scopus.com/pages/publications/85015852401
U2 - 10.1109/DataCloud.2016.004
DO - 10.1109/DataCloud.2016.004
M3 - Conference contribution
AN - SCOPUS:85015852401
T3 - Proceedings of DataCloud 2016: 7th International Workshop on Data-Intensive Computing in the Clouds - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis
SP - 1
EP - 8
BT - Proceedings of DataCloud 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 November 2016
ER -