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.
Abstract. Advance Reservations are an important concept to support QoS and Workflow Scheduling in Grid environments. However, the impact of reservations from the Grid on the performance of local schedulers is not yet known. Using discrete event simulations we evaluate the impact of reservations on planning-based resource management of standard batch jobs. Our simulations are based on a real trace from the parallel workload archive. By introducing a new option for scheduling reservations in planning-based resource management, less reservation requests are rejected. Our results are important for increasing the acceptability of the Grid technology. We show, that a limited number of additional resource reservations from the Grid have only a limited impact on the performance of the traditionally submitted batch jobs.
Cloud computing has already been adopted in a broad range of application domains. However, domains like the distributed development of embedded systems are still unable to benefit from the advancements of cloud computing. Besides general security concerns, a common obstacle often is the incompatibility between such applications and the cloud. In particular, if applications need direct access to hardware elements, cloud computing cannot be used.In this paper we describe an approach of a novel cloud layer called Hardware as a Service (HaaS), which allows for usage distinct hardware components through the Internet analogously to the cloud services. HaaS focuses the transparent integration of remote hardware that is distributed over multiple geographical locations into an operating system. Furthermore, HaaS will not only enable interconnection of physical systems, but also virtual hardware emulation. Therefore, we consider in this paper only the use of emulated hardware and the interconnection with hardware models. To demonstrate the tremendous improvement by a Haas cloud, we explain the applicability in a distributed development process by an anti blocking system and an adaptive cruise control system in the automotive industry.
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