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Many scienti c disciplines (e.g., biology, astrophysics, particle physics, earth sciences) are shifting from in vitro to in silico research a s m o r e p h ysical processes and natural phenomena are simulated in a computer (in silico) instead of being observed (in vitro). In many of these virtual laboratories, the computations involved are very complex and long lived. Currently, users are required to manually handle almost all aspects of such computations, including their dependability. Not surprisingly, this is a major bottleneck and a signi cant source of ineciencies. To address this issue, we h a ve d e v eloped BioOpera, an extensible process support management system for virtual laboratories. In this paper, we brie y discuss the architecture and functionality of BioOpera and show h o w it can be used to e ciently manage long lived complex computations.

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In this paper we present BioOpera, an extensible process support system for cluster-aware computing. It features an intuitive way to specify computations, as well as improved support for running them over a cluster, providing monitoring, persistence, fault tolerance and interaction capabilities without sacrificing efficiency and scalability.

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