Abstract
The German CMS community (DCMS) as a whole can benefit from the various compute resources, available to its different institutes. While Grid-enabled and National Analysis Facility resources are usually shared within the community, local and recently enabled opportunistic resources like HPC centers and cloud resources are not. Furthermore, there is no shared submission infrastructure available.Via HTCondor’s [1] mechanisms to connect resource pools, several remote pools can be connected transparently to the users and therefore used more efficiently by a multitude of user groups. In addition to the statically provisioned resources, also dynamically allocated resources from external cloud providers as well as HPC centers can be integrated. However, the usage of such dynamically allocated resources gives rise to additional complexity. Constraints on access policies of the resources, as well as workflow necessities have to be taken care of. To maintain a well-defined and reliable runtime environment on each resource, virtualization and containerization technologies such as virtual machines, Docker, and Singularity, are used.
Highlights
Recent surveys show that a significant amount of computing resources is locally available to institutes of the German high energy physics (HEP) community, not shared among the national collaborators
HTCondor Computing payloads are organized as jobs, which consist of an executable and possible input and output files, and these jobs are scheduled using batch systems
In combination with modern container technologies such as Docker or Singularity, this enables the usage of virtually any resource, non-HEP dedicated resources
Summary
Recent surveys show that a significant amount of computing resources is locally available to institutes of the German high energy physics (HEP) community, not shared among the national collaborators. Those resources, combined with the official WLCG [2] resources constitute a rather heterogeneous, challenging environment for administrators, as well as for users: For each resource there might be different access and usage policies, authorization and thereby authentication has to be handled, and the users expect a certain runtime environment in order to execute HEP workflows. Users submit jobs to their local HTCondor instance, which checks within the local pool for resources which match the requirements.
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