Synthetic Grid Workloads with Ibis, Koala, and Grenchmark (original) (raw)

On grid performance evaluation using synthetic workloads

… Strategies for Parallel …, 2007

Grid computing is becoming a common platform for solving large scale computing tasks. However, a number of major technical issues, including the lack of adequate performance evaluation approaches, hinder the grid computing’s further development. The requirements herefore are manifold; adequate approaches must combine appropriate performance metrics, realistic workload models, and flexible tools for workload generation, submission, and analysis. In this paper we present an approach to tackle this complex problem. First, we introduce a set of grid performance objectives based on traditional and grid-specific performance metrics. Second, we synthesize the requirements for realistic grid workload modeling, e.g. co-allocation, data and network management, and failure modeling. Third, we show how GrenchMark, an existing framework for generating, running, and analyzing grid workloads, can be extended to implement the proposed modeling techniques. Our approach aims to be an initial and necessary step towards a common performance evaluation framework for grid environments.

The Availability of Workloads for Grid Computing Environments

International journal of engineering research and technology, 2018

Grid Technology is a growing information technology field where the main purpose of grid is to build a kind of dynamic, distriuted and heterogeneous computing environment and realize collaborative resource sharing and problem solving in dynamic and multiple virtual organizations. It enables sharing, selection and aggregation of suitable computational and data resources for solving large-scale data intensive problems in science, engineering and commerce. To perform a study on grid scheduling or any other important concepts, acquiring a real grid environment is costly. To avoid that, we can use simulation tools. This paper provides the list of various simulation tools for grid computing together with the data sets collections. To perform a research based on grid computing environments, these tools and data sets explained in this paper are useful. Keywords—Grid computing, workload, simulation, Bricks, SimGrid, Monarc, GridNet, OptorSim, EcoGrid, GangSim, SimJava

Enabling Adaptive Grid Scheduling and Resource Management

Computing Research Repository, 2007

Wider adoption of the Grid concept has led to an increasing amount of federated computational, storage and visualisation resources being available to scientists and researchers. Distributed and heterogeneous nature of these resources renders most of the legacy cluster monitoring and management approaches inappropriate, and poses new challenges in workflow scheduling on such systems. Effective resource utilisation monitoring and highly granular