The maximal utilization of processor co-allocation in multicluster systems

In systems consisting of multiple clusters of processors which employ space sharing for scheduling jobs, such as our distributed ASCI supercomputer (DAS), co-allocation, i.e., the simultaneous allocation of processors to single jobs in multiple clusters, may be required. In studies of scheduling in single clusters it has been shown that the achievable (maximal) utilization may be much less than 100%, a problem that may be aggravated in multicluster systems. In this paper we study the maximal utilization when co-allocating jobs in multicluster systems, both with analytic means (we derive exact and approximate formulas when the service-time distribution is exponential), and with simulations with synthetic workloads and with workloads derived from the logs of actual systems

Performance Analysis of Processor Co-Allocation in Multicluster Systems

Electrical Engineering, Mathematics and Computer Scienc

Priorities among multiple queues for processor co-allocation in multicluster systems

In systems consisting of multiple clusters of processors which employ space sharing for scheduling jobs, such as our Distributed ASCI Supercomputer (DAS), co-allocation, i.e., the simultaneous allocation of processors to single jobs in multiple clusters, may be required. In order to handle both single-cluster (local) jobs and multi-cluster (global) jobs, such systems may have only local schedulers (which then need to be aware of the whole system), or only a single global scheduler or both, and each scheduler has its own queue. We assess with simulations the response times of both local and global jobs in multicluster systems for different configurations of queues, for different priority orders in which the associated schedulers are allowed to schedule jobs, and for different job-stream compositions

The maximal utilization of processor co-allocation in multicluster systems

In systems consisting of multiple clusters of processors which employ space sharing for scheduling jobs, such as our distributed ASCI supercomputer (DAS), co-allocation, i.e., the simultaneous allocation of processors to single jobs in multiple clusters, may be required. In studies of scheduling in single clusters it has been shown that the achievable (maximal) utilization may be much less than 100%, a problem that may be aggravated in multicluster systems. In this paper we study the maximal utilization when co-allocating jobs in multicluster systems, both with analytic means (we derive exact and approximate formulas when the service-time distribution is exponential), and with simulations with synthetic workloads and with workloads derived from the logs of actual systems

Hippocrates : a context-aware, collaboration enabling search tool

As the volume of medical literature is growing rapidly, search engines implementing the basic information retrieval model often fail to address the information needs of the medical professionals. In this paper we propose a search tool that aims to capture the information need of the clinical user by including concepts from the context in the searching process. Three different approaches were implemented and evaluated, the pre-filtering, the query expansion and the reranking. The system also supports Collaborative Information Seeking (CIS) through algorithmic and User Interface (UI) interventions. The returned citations on a given query are reranked based on the ratings that team members have assigned for similar cases making use of the scoring proposed by the ISpy system. The results from the evaluation of the proposed tool show that pre-filtering performed better than the alternative contextualization search approaches in terms of precision. Keywords: Context aware systems, Collaborative information seeking, Search tool, Information nee

The influence of the structure and sizes of jobs on the performance of co-allocation

Over the last decade, much research in the area of scheduling has concentrated on single cluster systems. Less attention has been paid to multicluster systems, although they are gaining more and more importance in practice. We propose a model for scheduling rigid jobs consisting of multiple components in multicluster systems by pure space sharing, based on the Distributed ASCI Supercomputer. Using simulations, we asses the in.uence of the structure and sizes of the jobs on the system’s performance, measured in terms of the average response time and the maximum utilization. We consider three types of requests, total requests, unordered requests and ordered requests, and compare their effect on the system’s performance for two scheduling policies, First Come First Served, and Fit Processors First Served, which allows the scheduler to look further in the queue for jobs that .t. These types of job requests are differentiated by the restrictions they impose on the scheduler and by the form of co-allocation used. The results show that the performance improves with decreasing average job size and when fewer restrictions are imposed on the scheduler

A process-oriented methodology for modelling cancer treatment trial protocols

Cancer-patient management in the context of a multi-center treatment trial requires following a complex detailed process involving multispecialty patient treatment as well as study-related tasks, described in free-text protocol documents. We present a process-oriented approach for modelling clinical trial treatment protocols (CTTPs) to be used for enabling applications that support protocol-based care process delivery, monitoring and analysis. This modelling approach provides an intuitive visual representation of the protocol document catering for change management, intra-center and national adaptations to the master protocol, and multi-level share-ability. The methodology can be re-used in CTTPs of different cancer domains due to the similarity of the CTTPs in terms of required content

A measurement-based simulation study of processor co-allocation in multicluster systems

In systems consisting of multiple clusters of processors interconnected by relatively slow network connections such as our Distributed ASCI Supercomputer (DAS), applications may benefit from the availability of processors in multiple clusters. However, the performance of single-application multicluster execution may be degraded due to the slow wide-area links. In addition, scheduling policies for such systems have to deal with more restrictions than schedulers for single clusters in that every component of a job has to fit in separate clusters. In this paper we present a measurement study of the total runtime of two applications, and of the communication time of one of them, both on single clusters and on multicluster systems. In addition, we perform simulations of several multicluster scheduling policies based on our measurement results. Our results show that in many cases, restricted forms of co-allocation in multiclusters have better performance than not allowing co-allocation at all

A process-oriented methodology for modelling cancer treatment trial protocols

Cancer-patient management in the context of a multi-center treatment trial requires following a complex detailed process involving multispecialty patient treatment as well as study-related tasks, described in free-text protocol documents. We present a process-oriented approach for modelling clinical trial treatment protocols (CTTPs) to be used for enabling applications that support protocol-based care process delivery, monitoring and analysis. This modelling approach provides an intuitive visual representation of the protocol document catering for change management, intra-center and national adaptations to the master protocol, and multi-level share-ability. The methodology can be re-used in CTTPs of different cancer domains due to the similarity of the CTTPs in terms of required content