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Cluster computing is excellent for parallel computation. It has become increasingly popular. In cluster computing, a service level agreement (SLA) is a set of quality of services (QoS) and a fee agreed between a customer and an application service provider. It plays an important role in an e-business application. An application service provider uses a set of cluster computing resources to support...
Co-allocation of performance-guaranteed computing and network resources provided by several administrative domains is one of the key issues for constructing a QoS-guaranteed Grid. We propose an advance reservation-based co-allocation algorithm for both computing and network resources on a QoS-guaranteed Grid, modeled as an integer programming (IP) problem. The goal of our algorithm is to create reservation...
To improve the resource utilization and satisfy more users, a Greedy Double Auction Mechanism(GDAM) is proposed to allocate resources in grid environments. GDAM trades resources at discriminatory price instead of uniform price, reflecting the variance in requirements for profits and quantities. Moreover, GDAM applies different auction rules to different cases, over-demand, over-supply and equilibrium...
The commercial exploitation of the emerging Grid and Cloud markets needs SLAs to sell computing run times. Job traces show that users have a limited ability to estimate the resource needs of their applications. This offers the possibility to apply overbooking to negotiation, but overbooking increases the risk of SLA violations. This work presents an overbooking approach with an integrated risk assessment...
In this paper, we address job scheduling in Distributed Computing Infrastructures, that is a loosely coupled network of autonomous acting High Performance Computing systems. In contrast to the common approach of mutual workload exchange, we consider the more intuitive operator’s viewpoint of load-dependent resource reconfiguration. In case of a site’s over-utilization, the scheduling system is able...
A crucial step in DNA sequence analysis is mapping short sequences generated by next-generation instruments to a reference genome. In this paper, we focus on efficient online scheduling of multi-user parallel short sequence mapping queries on a multiprocessor system. With the availability of parallel execution models, the problem at hand becomes a moldable task scheduling problem where the number...
We present the Dynamic Priority (DP) parallel task scheduler for Hadoop. It allows users to control their allocated capacity by adjusting their spending over time. This simple mechanism allows the scheduler to make more efficient decisions about which jobs and users to prioritize and gives users the tool to optimize and customize their allocations to fit the importance and requirements of their jobs...
This paper has been inspired by the study of the complex data set from the Czech National Grid MetaCentrum. Unlike other widely used workloads from Parallel Workloads Archive or Grid Workloads Archive, this data set includes additional information concerning machine failures, job requirements and machine parameters which allows to perform more realistic simulations. We show that large differences...
Many computational solutions can be expressed as directed acyclic graphs (DAGs) with weighted nodes. In parallel computing, scheduling such DAGs onto manycore processors remains a fundamental challenge, since synchronization across dozens of threads and preserving precedence constraints can dramatically degrade the performance. In order to improve scheduling performance on manycore processors, we...
Virtualization technology has introduced new ways for managing IT infrastructure. The flexible deployment of applications through self-contained virtual machine images has removed the barriers for multiplexing, suspending and migrating applications with their entire execution environment, allowing for a more efficient use of the infrastructure. These developments have given rise to an important challenge...
This paper proposes and evaluates APIs for Inter-Core Time Aggregation Scheduler (IAS). IAS is a kernel-level thread scheduler to enhance performance of multi-threaded programs on multi-core processors. IAS combines time-multiplexing and space-multiplexing scheduling to utilize caches existing per processing core and shared between processing cores. We present the effect of APIs in two aspects...
Job schedulers improve the system utilization by requiring users to estimate how long their jobs will run and by using this information to better pack (or “backfill”) the jobs. But, surprisingly, many studies find that deliberately making estimates less accurate boosts (or does not affect) the performance, which helps explain why production systems still exclusively rely on notoriously inaccurate...
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