Results 1 -
8 of
8
ZENTURIO: An Experiment Management System for Cluster and Grid Computing
- In Proceedings of the 4th International Conference on Cluster Computing (CLUSTER 2002
, 2002
"... The need to conduct and manage large sets of experiments for scientific applications dramatically increased over the last decade. However, there is still very little tool support for this complex and tedious process. In this paper we introduce the ZENTURIO experiment management system for parameter ..."
Abstract
-
Cited by 15 (3 self)
- Add to MetaCart
(Show Context)
The need to conduct and manage large sets of experiments for scientific applications dramatically increased over the last decade. However, there is still very little tool support for this complex and tedious process. In this paper we introduce the ZENTURIO experiment management system for parameter studies, performance analysis, and software testing for cluster and Grid architectures. ZENTURIO uses the ZEN directive-based language to specify arbitrary complex program executions. ZENTURIO is designed as a collection of Grid services that comprise: (1) a registry service which supports registering and locating Grid services; (2) an experiment generator that parses files with ZEN directives and instruments applications for performance analysis and parameter studies; (3) an experiment executor that compiles and controls the execution of experiments on the target machine. A graphical user portal allows the user to control and monitor the experiments and to automatically visualise performance and output data across multiple experiments. ZENTURIO has been implemented based on Java/Jini distributed technology. It supports experiment management on cluster architectures via PBS and on Grid infrastructures through GRAM. We report results of using ZENTURIO for performance analysis of an ocean simulation application and a parameter study of a computational finance code.
From Web Services to OGSA: Experiences in Implementing an OGSA-based Grid Application
- 4th International Workshop on Grid Computing
, 2003
"... In previous work we have presented the ZENTURIO experiment management system for performance and parameter studies of parallel and distributed applications on cluster and Grid architectures. In this paper we describe experiences of an on-going work, targeting the implementation of ZENTURIO on top of ..."
Abstract
-
Cited by 5 (0 self)
- Add to MetaCart
(Show Context)
In previous work we have presented the ZENTURIO experiment management system for performance and parameter studies of parallel and distributed applications on cluster and Grid architectures. In this paper we describe experiences of an on-going work, targeting the implementation of ZENTURIO on top of the Open Grid Services Architecture (OGSA). We analyse the opportunities offered by a Web services toolkit to develop Grid services as required by OGSA and compare them with the solutions offered by the Open Grid Services Infrastructure (OGSI) specification. Issues regarding proxy management, service lifecycle, UDDI service repository, firewall management, Factory and Registry services, service throughput, and security are comparatively analysed in both implementations.
On Using ZENTURIO for Performance and Parameter Studies on Cluster and Grid Architectures
- Proc. 11 th Euromicro Conference on Parallel Distributed Network-based Processing (PDP2003), Genua
, 2003
"... Over the last decade, a dramatic increase has been observed in the need for generating and organising data in the course of large parameter studies, performance analysis, and software testings. We have developed the ZENTURIO experiment management tool for performance and parameter studies on cluster ..."
Abstract
-
Cited by 5 (0 self)
- Add to MetaCart
(Show Context)
Over the last decade, a dramatic increase has been observed in the need for generating and organising data in the course of large parameter studies, performance analysis, and software testings. We have developed the ZENTURIO experiment management tool for performance and parameter studies on cluster and Grid architectures. In this paper we describe our experience with ZENTURIO for performance and parameter studies of a material science kernel, a three-dimensional particle-in-cell simulation, a fast fourier transform, and a financial modeling application. Experiments have been conducted on an SMP cluster with Fast Ethernet and Myrinet communication networks, using PBS (Portable Batch System) and GRAM (Globus Resource Allocation Manager) as job managers.
A Web Service-based Experiment Management System for the Grids
- In 17th International Parallel and Distributed Processing Symposium (IPDPS 2003
, 2002
"... We have developed ZENTURIO, which is an experiment management system for performance and parameter studies as well as software testing for cluster and Grid architectures. In this paper we describe our experience with developing ZENTURIO as a collection of Web services. A directivebased language call ..."
Abstract
-
Cited by 4 (1 self)
- Add to MetaCart
We have developed ZENTURIO, which is an experiment management system for performance and parameter studies as well as software testing for cluster and Grid architectures. In this paper we describe our experience with developing ZENTURIO as a collection of Web services. A directivebased language called ZEN is used to annotate arbitrary les and specify arbitrary application parameters. An Experiment Generator Web service parses annotated application les and generates appropriate codes for experiments. An Experiment Executor Web service compiles, executes, and monitors experiments on a single or a set of local machines on the Grid. Factory and Registry services are employed to create and register Web services, respectively. An event infrastructure has been customised to support high-level events under ZENTURIO in order to avoid expensive polling and to detect important system and application status information. A graphical user portal allows the user to generate, control, and monitor experiments. We compare our design with the Open Grid Service Architecture (OGSA) and highlight similarities and dierences. We report results of using ZENTURIO to conduct performance analysis of a material science code that executes on the Grid under the Globus Grid infrastructure.
An Automated Approach to Create, Store, and Analyze Large-scale Experimental Data in Clouds
"... Abstract—The flexibility and scalability of computing clouds make them an attractive application migration target; yet, the cloud remains a black-box for the most part. In particular, their opacity impedes the efficient but necessary testing and tuning prior to moving new applications into the cloud ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Abstract—The flexibility and scalability of computing clouds make them an attractive application migration target; yet, the cloud remains a black-box for the most part. In particular, their opacity impedes the efficient but necessary testing and tuning prior to moving new applications into the cloud. A natural and presumably unbiased approach to reveal the cloud’s complexity is to collect significant performance data by conduct-ing more experimental studies. However, conducting large-scale system experiments is particularly challenging because of the practical difficulties that arise during experimental deployment, configuration, execution and data processing. In this paper we address some of these challenges through Expertus – a flexible automation framework we have developed to create, store and analyze large-scale experimental measurement data. We create performance data by automating the measurement processes for large-scale experimentation, including: the application de-ployment, configuration, workload execution and data collection processes. We have automated the processing of heterogeneous data as well as the storage of it in a data warehouse, which we have specifically designed for housing measurement data. Finally, we have developed a rich web portal to navigate, statistically analyze and visualize the collected data. Expertus combines template-driven code generation techniques with aspect-oriented programming concepts to generate the necessary resources to fully automate the experiment measurement process. In Expertus, a researcher provides only the high-level description about the experiment, and the framework does everything else. At the end, the researcher can graphically navigate and process the data in the web portal.
SUMMARY
"... Performance engineering of parallel and distributed applications is a complex task that iterates through various phases, ranging from modeling and prediction, to performance measurement, experiment management, data collection, and bottleneck analysis. There is no evidence so far that all of these ph ..."
Abstract
- Add to MetaCart
(Show Context)
Performance engineering of parallel and distributed applications is a complex task that iterates through various phases, ranging from modeling and prediction, to performance measurement, experiment management, data collection, and bottleneck analysis. There is no evidence so far that all of these phases should/can be integrated in a single monolithic tool. Moreover, the emergence of computational Grids as a common single wide-area platform for high-performance computing raises the idea to provide performance tools and others as interacting Grid services that share resources, support interoperability among different users and tools, and most important provide omni-present performance functionality over the Grid. We have developed the ASKALON tool set [18] to support performance-oriented development of parallel and distributed (Grid) applications. ASKALON comprises four tools, coherently integrated into a Grid service-based distributed architecture. SCALEA is a performance instrumentation, measurement, and analysis tool of parallel and distributed applications. ZENTURIO is a general purpose experiment management tool with advanced support for multi-experiment performance analysis and parameter studies. AKSUM provides semi-automatic high-level performance bottleneck detection through a special-purpose performance property specification language. The PerformanceProphet enables the user to model and predict the performance of parallel applications at early development stages.
2012 IEEE Fifth International Conference on Cloud Computing Expertus: A Generator Approach to Automate Performance Testing in IaaS Clouds
"... Abstract—Cloud computing is an emerging technology paradigm that revolutionizes the computing landscape by providing on-demand delivery of software, platform, and infrastructure over the Internet. Yet, architecting, deploying, and configuring enterprise applications to run well on modern clouds rema ..."
Abstract
- Add to MetaCart
Abstract—Cloud computing is an emerging technology paradigm that revolutionizes the computing landscape by providing on-demand delivery of software, platform, and infrastructure over the Internet. Yet, architecting, deploying, and configuring enterprise applications to run well on modern clouds remains a challenge due to associated complexities and non-trivial implications. The natural and presumably unbiased approach to these questions is thorough testing before moving applications to production settings. However, thorough testing of enterprise applications on modern clouds is cumbersome and error-prone due to a large number of relevant scenarios and difficulties in testing process. We address some of these challenges through Expertus—a flexible code generation framework for automated performance testing of distributed applications in Infrastructure as a Service (IaaS) clouds. Expertus uses a multi-pass compiler approach and leverages template-driven code generation to modularly incorporate different software applications on IaaS clouds. Expertus automatically handles complex configuration dependencies of software applications and significantly reduces human errors associated with manual approaches for software configuration and testing. To date, Expertus has been used to study three distributed applications on five IaaS clouds with over 10,000 different hardware, software, and virtualization configurations. The flexibility and extensibility of Expertus and our own experience on using it shows that new clouds, applications, and software packages can easily be incorporated.
An Infrastructure for Automating Large-scale Performance Studies and Data Processing
"... Abstract—The Cloud has enabled the computing model to shift from traditional data centers to publicly shared computing infrastructure; yet, applications leveraging this new computing model can experience performance and scalability issues, which arise from the hidden complexities of the cloud. The m ..."
Abstract
- Add to MetaCart
(Show Context)
Abstract—The Cloud has enabled the computing model to shift from traditional data centers to publicly shared computing infrastructure; yet, applications leveraging this new computing model can experience performance and scalability issues, which arise from the hidden complexities of the cloud. The most reliable path for better understanding these complexities is an empirically based approach that relies on collecting data from a large number of performance studies. Armed with this performance data, we can understand what has happened, why it happened, and more importantly, predict what will happen in the future. However, this approach presents challenges itself, namely in the form of data management. We attempt to mitigate these data challenges by fully automating the performance measurement process. Concretely, we have developed an automated infrastructure, which reduces the complexity of the large-scale performance measurement process by generating all the necessary resources to conduct experiments, to collect and process data and to store and analyze data. In this paper, we focus on the performance data management aspect of our infrastructure.
