Authors:
Arnaud Bonnaffoux
1
;
Eddy Caron
2
;
Hadrien Croubois
2
and
Olivier Gandrillon
3
Affiliations:
1
Univ. Lyon, ENS de Lyon, Univ. Claude Bernard and Cosmo Tech, France
;
2
ENS de Lyon, France
;
3
Univ. Lyon, ENS de Lyon and Univ. Claude Bernard, France
Keyword(s):
Auto-Scaling, Resource Management, Workflow, Cloud, Scientific applications, HPC
Related
Ontology
Subjects/Areas/Topics:
Cloud Brokering
;
Cloud Computing
;
Services Science
Abstract:
With the recent development of commercial Cloud offers, Cloud solutions are today the obvious solution for
many computing use-cases. However, high performance scientific computing is still among the few domains
where Cloud still raises more issues than it solves. Notably, combining the workflow representation of complex
scientific applications with the dynamic allocation of resources in a Cloud environment is still a major
challenge. In the meantime, users with monolithic applications are facing challenges when trying to move
from classical HPC hardware to elastic platforms. In this paper, we present the structure of an autonomous
workflow manager dedicated to IaaS-based Clouds (Infrastructure as a Service) with DaaS storage services
(Data as a Service). The solution proposed in this paper fully handles the execution of multiple workflows on
a dynamically allocated shared platform. As a proof of concept we validate our solution through a biologic
application with the WASABI workflow.