Abstract. Nearly all existing HPC systems are operated by resource management systems based on the queuing approach. With the increasing acceptance of grid middleware like Globus, new requirements for the underlying local resource management systems arise. Features like advanced reservation or quality of service are needed to implement high level functions like co-allocation. However it is difficult to realize these features with a resource management system based on the queuing concept since it considers only the present resource usage. In this paper we present an approach which closes this gap. By assigning start times to each resource request, a complete schedule is planned. Advanced reservations are now easily possible. Based on this planning approach functions like diffuse requests, automatic duration extension, or service level agreements are described. We think they are useful to increase the usability, acceptance and performance of HPC machines. In the second part of this paper we present a planning based resource management system which already covers some of the mentioned features.
Workstation clusters are often not only used for high-throughput computing in time-sharing mode but also for running complex parallel jobs in space-sharing mode. This poses several difficulties to the resource management system, which must be able to reserve computing resources for exclusive use and also to determine an optimal process mapping for a given system topology. On the basis of our CCS software, we describe the anatomy of a modern resource management system. Like Codine, Condor, and LSF, CCS provides mechanisms for the user-friendly system access and management of clusters. But unlike them, CCS is targeted at the effective support of space-sharing parallel and even metacomputers. Among other features, CCS provides a versatile resource description facility, topology-based process mapping, pluggable schedulers, and hooks to metacomputer management.
We present a software system for the management of geographically distributed highperformance computers. It consists of three components: 1. The Computing Center Software (CCS) is a vendor-independent resource management software for local HPC systems. It controls the mapping and scheduling of interactive and batch jobs on massively parallel systems; 2. The Resource and Service Description (RSD) is used by CCS for specifying and mapping hardware and software components of (meta-)computing environments. It has a graphical user interface, a textual representation and an object-oriented API; 3. The Service Coordination Layer (SCL) co-ordinates the co-operative use of resources in autonomous computing sites. It negotiates between the applications' requirements and the available system services.
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